VRPRD_ORTools.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# OR Tools for Robot & Drone VRP"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### **目標**\n",
    "\n",
    "比較 **VRP**、**Drone VR**、**Robot VRP**、**Drone & Robot VRP**，四種組合在不同參數下的表現\n",
    "\n",
    "- **表現指標**: 總路徑時間, 總路徑長度, 時間複雜度, 空間複雜度 \n",
    "\n",
    "##### **參數**\n",
    "- 不同地圖大小 (5x5, 10x10, 15x15, 20x20, 25x25)\n",
    "- 不同客戶數量 (210, 180, 150, 130, 110): 從 30 次的重複模擬實驗結果取平均, 趨近於 8 小時的 Nodes 數量\n",
    "- 1 台車\n",
    "- 蒙地卡羅模擬次數 10 次以上\n",
    "\n",
    "##### **實驗假設**\n",
    "\n",
    "- 每個客戶點的貨物數量、尺寸皆相同\n",
    "- 每個客戶點的服務時間皆為 2 分鐘\n",
    "- 實驗載具共有 Truck、Drone 與 Robot 三種載具\n",
    "- 一台 Truck 配置 1 台 Drone 與 Robot，且 Drone 與 Robot 可以同時在路上跑\n",
    "- Drone 與 Robot 可以由 Truck 於任意客戶點中派出與回收，派出與回收各需要花費 1 分鐘\n",
    "- Truck 可以多次派出 Drone 與 Robot\n",
    "- 若 Truck 抵達回收點時 Drone 與 Robot 尚未返回，需記錄等待時間\n",
    "- 司機可以有等待時間，但不能提前 10 分鍾以上到達\n",
    "- Truck 載具的速度為 60 km/hr，使用曼哈頓距離計算，載貨量為 **服務點 ÷ 車輛數** (考量平均工作量)\n",
    "- Drone 載具的速度為 80 km/hr，使用歐式距離計算，每次只能載 1 個貨物, 電池續航力為 60 分鐘\n",
    "- Robot 載具的速度為 60 km/hr，使用曼哈頓距離計算，每次只能載 4 個貨物, 電池續航力為 120 分鐘\n",
    "\n",
    "##### **Drone 挑選方法說明**\n",
    "\n",
    "- 以 OR-Tools 初始解分組, 找出每組中最適合派給 Drone 的點\n",
    "- 篩選出最近點距離最遠的 n 個點作為 Drone 效益最高的點, n 設定為 25 百分位數\n",
    "- 設定其原路徑為 Drone 的可能發收站, 並排除掉 Node 為其他 Drone 發收站的點\n",
    "\n",
    "##### **Robot 挑選方法**\n",
    "\n",
    "- 從 Initial Solution 中抓出最短的路徑組合 (10 個造訪點一組, 如數量 <= 10 則不考慮出車)\n",
    "- 路徑組合的造訪時間不可超過 Robot 電池續航力\n",
    "- 根據距離排序, 排除掉 Node 重複的組合\n",
    "- 篩選出前 25 百分位數近的組合"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "import random as rd\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import math\n",
    "import copy as copy\n",
    "# OR-Tools\n",
    "from ortools.constraint_solver import routing_enums_pb2 \n",
    "from ortools.constraint_solver import pywrapcp \n",
    "# Record time & space complexity\n",
    "import time \n",
    "import tracemalloc\n",
    "# Visualization\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "sns.set()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Parameters: 實驗參數設定"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "# [實驗控制變數] \n",
    "# 地圖大小(km) | 服務點數量 | 車輛數量\n",
    "# MAX_X, MAX_Y = 20, 20\n",
    "# NUM_NODES = 30\n",
    "# NUM_VEHICLES = 1\n",
    "\n",
    "# 站點服務時間\n",
    "SERVICE_TIME = 2\n",
    "\n",
    "# [Truck]\n",
    "# 時速 60km | 每台車有最大移動距離(固定) | 貨物重量相同 | 本實驗不考慮車輛成本, 故每台車可載貨物數量 = (站點/車輛數)\n",
    "VEHICLE_SPEED = 60\n",
    "# VEHICLE_CAPACITIES = int(NUM_NODES / NUM_VEHICLES)\n",
    "\n",
    "# [Drone]\n",
    "# 時速 80km | 續航力 60 min | 採用歐幾里德距離 | 負責離群值 | 派出與收回載具各需要 1 分鐘 (總共2)\n",
    "DRONE_CAPACITIES = 1\n",
    "DRONE_SPEED = 80\n",
    "DRONE_BATTERY_LIFE = 60\n",
    "DRONE_DISPATCH_TIME = 1\n",
    "FILTER_RATE = \n",
    "\n",
    "# [Robot]\n",
    "# 時速 30km | 續航力 120 min | 負責高密度點 | 派出與收回載具各需要 1 分鐘 (總共2)\n",
    "ROBOT_CAPACITIES = 10\n",
    "ROBOT_SPEED = 60\n",
    "ROBOT_BATTERY_LIFE = 120\n",
    "ROBOT_DISPATCH_TIME = 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model: 資料層設定"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 模擬實驗需求, 函式需帶入控制變數\n",
    "# **controls = dict(map_size=(20, 20), num_nodes=20, num_vehicles=1)\n",
    "def create_data_model(**controls):\n",
    "    \n",
    "    NUM_NODES = controls[\"num_nodes\"]\n",
    "    MAX_X, MAX_Y = controls[\"map_size\"][0], controls[\"map_size\"][1]\n",
    "    NUM_VEHICLES = controls[\"num_vehicles\"]\n",
    "    VEHICLE_CAPACITIES = controls[\"num_nodes\"] // controls[\"num_vehicles\"] # 如果非整數需分配給其他車輛\n",
    "    \n",
    "    data = {}\n",
    "    data[\"num_locations\"] = [(round(np.random.uniform(0, MAX_X), 3), round(np.random.uniform(0, MAX_Y), 3)) for i in range(NUM_NODES)]\n",
    "    data[\"num_locations\"][0] = (round((MAX_X / 2), 3), round((MAX_Y / 2), 3)) \n",
    "    data[\"distance_matrix\"] = compute_manhattan_distance_matrix(data[\"num_locations\"]) # 距離矩陣必須為整數, 否則無法在 OR-Tools 中求解\n",
    "    data[\"e_distance_matrix\"] = compute_euclidean_distance_matrix(data[\"num_locations\"]) # 歐幾里德距離, 取小數第二位(drone 使用)\n",
    "    data[\"time_matrix\"] = compute_time_matrix(data[\"distance_matrix\"]) # 最小單位分鐘\n",
    "    data[\"num_nodes\"] = NUM_NODES\n",
    "    data[\"num_vehicles\"] = NUM_VEHICLES\n",
    "    data[\"depot\"] = 0 # Depot 的索引值\n",
    "    data[\"time_windows\"] = []\n",
    "    data[\"initial_routes\"] = [] # 如果有初始解可以套用\n",
    "    data[\"demands\"] = [1 for i in range(NUM_NODES)]\n",
    "    data[\"demands\"][0] = 0\n",
    "    data[\"vehicle_capacities\"] = [VEHICLE_CAPACITIES for i in range(NUM_VEHICLES)]\n",
    "    if NUM_NODES % VEHICLE_CAPACITIES > 0:\n",
    "        for i in range(NUM_NODES % VEHICLE_CAPACITIES):\n",
    "            data[\"vehicle_capacities\"][i] += 1\n",
    "    # 三個載具負責的 node 索引值\n",
    "    data[\"vehicle\"] = []\n",
    "    data[\"drone\"] = []\n",
    "    data[\"robot\"] = []    \n",
    "    return data\n",
    "\n",
    "# 曼哈頓距離矩陣, truck & robot 用 (單位使用 m, 小於 1km 的距離會無法解題)\n",
    "def compute_manhattan_distance_matrix(nodes):\n",
    "    distance_matrix = []\n",
    "    for node_i in nodes:\n",
    "        distances = []\n",
    "        for node_j in nodes:\n",
    "            if node_i == node_j:\n",
    "                distances.append(0)\n",
    "            else:\n",
    "                manhattan_distance = np.sum(np.abs(np.array(node_i) - np.array(node_j)))\n",
    "                distances.append(int(manhattan_distance * 1000))\n",
    "        distance_matrix.append(distances)\n",
    "    return distance_matrix\n",
    "\n",
    "# 歐式距離矩陣, drone 使用 (單位 m)\n",
    "def compute_euclidean_distance_matrix(nodes):\n",
    "    distance_matrix = []\n",
    "    for node_i in nodes:\n",
    "        distances = []\n",
    "        for node_j in nodes:\n",
    "            if node_i == node_j:\n",
    "                distances.append(0)\n",
    "            else:\n",
    "                euclidean_distance = np.sqrt((node_i[0] - node_j[0])**2 + (node_i[1] - node_j[1])**2)\n",
    "                distances.append(int(euclidean_distance * 1000))\n",
    "        distance_matrix.append(distances)\n",
    "    return distance_matrix\n",
    "\n",
    "# 距離矩陣轉換為時間矩陣 (兩點花費分鐘 = 公里 / 時速 * 60)\n",
    "def compute_time_matrix(distance_matrix):\n",
    "    time_matrix = []\n",
    "    for i in distance_matrix:\n",
    "        time_matrix.append(list(map(lambda x: round(x / 1000 / VEHICLE_SPEED * 60, 3), i)))\n",
    "    return time_matrix"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Controller: 控制層設定"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 取得目標值(時間和/分鐘): 提供路徑, 速度, 參考距離矩陣, 會考量每個點的服務時間\n",
    "def get_objective_value(data, route, speed=VEHICLE_SPEED, matrix='distance_matrix'):\n",
    "    objective_value = 0\n",
    "    for i in range(len(route) - 1):\n",
    "        objective_value += (data[matrix][route[i]][route[i + 1]] / 1000) + SERVICE_TIME # 該點服務時間\n",
    "    objective_value = objective_value / speed * 60\n",
    "    return round(objective_value, 3)\n",
    "\n",
    "# 計算路徑總距離\n",
    "def get_total_distance(data, route):\n",
    "    total_dist = 0\n",
    "    for i in range(len(route) - 1):\n",
    "        total_dist += data['distance_matrix'][route[i]][route[i + 1]]\n",
    "    return round(total_dist, 3)\n",
    "\n",
    "# 計算每台車的總等待時間\n",
    "def get_waiting_time(data, routes, sidekick_routes, name):\n",
    "    assert name == 'drone' or name == 'robot'\n",
    "    # print(f'Vehicle: \\n{name}')\n",
    "    total = 0\n",
    "    waiting_time_list = [[] for i in range(len(sidekick_routes))]\n",
    "    for i, group in enumerate(sidekick_routes):\n",
    "        for j, r_s in enumerate(group): # 每筆路徑\n",
    "            if name == 'drone':\n",
    "                dur_s = get_objective_value(data, r_s, DRONE_SPEED, 'e_distance_matrix')\n",
    "            elif name == 'robot':\n",
    "                dur_s = get_objective_value(data, r_s, ROBOT_SPEED, 'distance_matrix')\n",
    "            start, end = r_s[0], r_s[-1]\n",
    "            r_v = routes[i][routes[i].index(start):routes[i].index(end)+1]\n",
    "            dur_v = get_objective_value(data, r_v, VEHICLE_SPEED)      \n",
    "            # print(f'Sidekick: {r_s}, Vehicle: {r_v}')\n",
    "            # print(f'-T(s): {dur_s}, T(v): {dur_v}')\n",
    "            if dur_s > dur_v: # 如果 sidekick 時間比較長, 記錄為等待時間\n",
    "                # print('-Wait for:', (dur_s - dur_v))\n",
    "                waiting_time_list[i].append(round(dur_s - dur_v, 3))  \n",
    "                total += (dur_s - dur_v)\n",
    "            else:\n",
    "                waiting_time_list[i].append(0)\n",
    "        if waiting_time_list[i] == []:\n",
    "            waiting_time_list[i] = [0]\n",
    "    return waiting_time_list\n",
    "\n",
    "# 計算每台車輛的總服務時間: 目標值 + 等待時間 + 收放時間; VRP 問題不會有等待時間\n",
    "def get_travelling_time(data, routes, drone_waiting=[], robot_waiting=[]):\n",
    "\n",
    "    total_dist, total_time, total_waiting  = [], [], []\n",
    "\n",
    "    for index, route in enumerate(routes):\n",
    "        dist = get_total_distance(data, route)\n",
    "        dur_v = get_objective_value(data, route)\n",
    "        waiting = 0\n",
    "\n",
    "        if len(drone_waiting) > 0:\n",
    "            dur_v += np.sum(drone_waiting[index])\n",
    "            waiting += np.sum(drone_waiting[index])\n",
    "\n",
    "        if len(robot_waiting) > 0:\n",
    "            dur_v += np.sum(robot_waiting[index])\n",
    "            waiting += np.sum(robot_waiting[index])\n",
    "\n",
    "        total_dist.append(round(dist, 3))\n",
    "        total_time.append(round(dur_v, 3))\n",
    "        total_waiting.append(round(waiting, 3))\n",
    "        print(f'Vehicle {index}: {dist} m, {round(dur_v, 3)} min, including {round(waiting, 3)} mins waiting time.')\n",
    "\n",
    "    print(f'Total distance of all routes: : {np.sum(total_dist)} m')\n",
    "    print(f'Maximum travel time: {round(max(total_time), 3)} min')\n",
    "    return total_dist, total_time, total_waiting\n",
    "\n",
    "# 計算派遣載具時間(1+1 = 2)\n",
    "def get_dispatch_time(routes):\n",
    "    dispatch_time = []\n",
    "    for i, group in enumerate(routes):\n",
    "        dispatch_time.append(len(group) * 2)\n",
    "    return dispatch_time\n",
    "\n",
    "# 重置 Node 的貨物需求\n",
    "def reset_demands(data, **controls):\n",
    "\n",
    "    NUM_VEHICLES = controls[\"num_vehicle\"]\n",
    "    VEHICLE_CAPACITIES = int(controls[\"num_nodes\"] / controls[\"num_vehicle\"])\n",
    "    data[\"demands\"] = [1 for i in range(data[\"num_nodes\"])]\n",
    "    data[\"demands\"][0] = 0\n",
    "    data[\"vehicle_capacities\"] = [VEHICLE_CAPACITIES for i in range(NUM_VEHICLES)]\n",
    "    return data\n",
    "\n",
    "def print_solution(data, manager, routing, solution):\n",
    "    \"\"\"Prints solution on console.\"\"\"\n",
    "    print(f\"Objective: {solution.ObjectiveValue()}\")\n",
    "    total_distance = 0\n",
    "    total_load = 0\n",
    "\n",
    "    for vehicle_id in range(data[\"num_vehicles\"]):\n",
    "        index = routing.Start(vehicle_id)\n",
    "        plan_output = f\"Route for vehicle {vehicle_id}:\\n\"\n",
    "        route_distance = 0\n",
    "        route_load = 0\n",
    "        while not routing.IsEnd(index):\n",
    "            node_index = manager.IndexToNode(index)\n",
    "            route_load += data[\"demands\"][node_index]\n",
    "            plan_output += f\" {node_index} ({route_distance}) -> \"\n",
    "            previous_index = index\n",
    "            index = solution.Value(routing.NextVar(index))\n",
    "            route_distance += routing.GetArcCostForVehicle(\n",
    "                previous_index, index, vehicle_id\n",
    "            )\n",
    "        plan_output += f\" {manager.IndexToNode(index)} ({route_distance})\\n\"\n",
    "        plan_output += f\"Distance of the route: {route_distance} km\\n\"\n",
    "        plan_output += f\"Load of the route: {route_load}\\n\"\n",
    "        print(plan_output)\n",
    "        total_distance += route_distance\n",
    "        total_load += route_load\n",
    "    \n",
    "    print(f\"Total distance of all routes: {total_distance} km\")\n",
    "    print(f\"Total load of all routes: {total_load}\")\n",
    "\n",
    "# Save routes to a list or array\n",
    "def get_routes(solution, routing, manager):\n",
    "    \"\"\"Get vehicle routes from a solution and store them in an array.\"\"\"\n",
    "    # Get vehicle routes and store them in a two dimensional array whose\n",
    "    # i,j entry is the jth location visited by vehicle i along its route.\n",
    "    routes = []\n",
    "    for route_nbr in range(routing.vehicles()):\n",
    "        index = routing.Start(route_nbr)\n",
    "        route = [manager.IndexToNode(index)]\n",
    "        while not routing.IsEnd(index):\n",
    "            index = solution.Value(routing.NextVar(index))\n",
    "            route.append(manager.IndexToNode(index))\n",
    "        routes.append(route)\n",
    "    return routes\n",
    "\n",
    "# OR Tools = manager + routing + search_parameter = solution\n",
    "def solve_routing_problem(data):\n",
    "    ''' 路徑管理員 RoutingIndexManager '''\n",
    "    # data 中有新資料需於此處引用\n",
    "    manager = pywrapcp.RoutingIndexManager(\n",
    "        len(data[\"distance_matrix\"]), data[\"num_vehicles\"], data[\"depot\"]\n",
    "    )\n",
    "    ''' 路徑資料 RoutingModel '''\n",
    "    routing = pywrapcp.RoutingModel(manager)\n",
    "    # 計算 node 貨物需求的工具\n",
    "    def demand_callback(from_index):\n",
    "        from_node = manager.IndexToNode(from_index)\n",
    "        return data[\"demands\"][from_node]\n",
    "\n",
    "    demand_callback_index = routing.RegisterUnaryTransitCallback(demand_callback)\n",
    "    routing.AddDimensionWithVehicleCapacity(\n",
    "        demand_callback_index,\n",
    "        0,  # null capacity slack\n",
    "        data['vehicle_capacities'],  # vehicle maximum capacities\n",
    "        False,  # start cumul to zero\n",
    "        \"Capacity\",\n",
    "    )\n",
    "\n",
    "    # 計算 node 間距離單位的工具, 調整距離計算方法可從函式 return 中修改\n",
    "    def distance_callback(from_index, to_index):\n",
    "        from_node = manager.IndexToNode(from_index) # 取得開始到結束點的索引值\n",
    "        to_node = manager.IndexToNode(to_index)\n",
    "        return data[\"distance_matrix\"][from_node][to_node] # 若題目為 VRPTW 需回傳 data[\"time_matrix\"]\n",
    "\n",
    "    transit_callback_index = routing.RegisterTransitCallback(distance_callback) # 設定所有車輛距離(arc)間的評估單位\n",
    "    routing.SetArcCostEvaluatorOfAllVehicles(transit_callback_index)\n",
    "    # routing.SetArcCostEvaluatorOfVehicle() # 打開後可定義其他車輛距離的評估單位\n",
    "\n",
    "    # 設定車輛行駛中累積的變量, VRPTW 時需將 demension_name 調整為 \"Time\"\n",
    "    routing.AddDimension(\n",
    "        transit_callback_index,\n",
    "        0,  # 車輛最大等待時間, VRPTW 用\n",
    "        999999999,  # 車輛最大行駛距離\n",
    "        False,  # 每輛車路線開始時，累計變數是否設為零 (VRPTW 時需調整為 False, 讓時間可累積)\n",
    "        \"Distance\",\n",
    "    )\n",
    "    distance_dimension = routing.GetDimensionOrDie(\"Distance\")\n",
    "    # distance_dimension.SetGlobalSpanCostCoefficient(0) # 成本係數設定成 100 會無法跑少數量的車輛路線\n",
    "\n",
    "    # 設計懲罰項: AddDisjuntion() 只能呼叫一次, 要將 node 排除在路徑中需要調整 Capacity\n",
    "    penalty = 100000\n",
    "    for node in range(1, len(data[\"distance_matrix\"])):\n",
    "        routing.AddDisjunction([manager.NodeToIndex(node)], penalty)\n",
    "\n",
    "    # 平衡車輛 loading, 避免部分車輛跑有路線\n",
    "    for vehicle_id in range(data['num_vehicles']):\n",
    "        routing.SetVehicleUsedWhenEmpty(True, vehicle_id)\n",
    "\n",
    "    routing.AddConstantDimension(\n",
    "        1, # +1 for each visit (note start node is counted so unused vehicle is still 1)\n",
    "        data[\"num_nodes\"] // data[\"num_vehicles\"] + 2, # max visit allowed,  hard limit\n",
    "        True,  # start cumul to zero\n",
    "        \"Counter\")\n",
    "        \n",
    "    counter_dimension = routing.GetDimensionOrDie(\"Counter\")\n",
    "    for vehicle_id in range(manager.GetNumberOfVehicles()):\n",
    "        index = routing.End(vehicle_id)\n",
    "        counter_dimension.SetCumulVarSoftLowerBound(index, 2, 100000) # penalty of 100000 for each empty vehicle since counter will be 1 aka (2 - 1) * 100_000  \n",
    "\n",
    "    ''' 啟發式演算法參數 search_parameters '''\n",
    "    search_parameters = pywrapcp.DefaultRoutingSearchParameters()\n",
    "    search_parameters.first_solution_strategy = (\n",
    "        routing_enums_pb2.FirstSolutionStrategy.PATH_CHEAPEST_ARC # 最快求解法, 預設為 PATH_CHEAPEST_ARC '''\n",
    "    )\n",
    "    search_parameters.local_search_metaheuristic = (\n",
    "        routing_enums_pb2.LocalSearchMetaheuristic.GUIDED_LOCAL_SEARCH     # 開啟後會改用 guided local search 求解 local minimum (GREEDY_DESCENT, TABU_SEARCH, Simulated Annealing...)\n",
    "    )\n",
    "    # search_parameters.time_limit.seconds = 5 # 搜尋時間限制\n",
    "    # search_parameters.log_search = True # 開啟後會顯示每次搜尋迭代(log)\n",
    "    search_parameters.solution_limit = 100 # 解決方案限制\n",
    "    \n",
    "    routing.CloseModelWithParameters(search_parameters) # 提供初始解時關閉搜尋參數\n",
    "    # initial_solution = routing.ReadAssignmentFromRoutes(data[\"initial_routes\"], True) # 求解前如果想提供初始路徑解可打開\n",
    "\n",
    "    solution = routing.SolveWithParameters(search_parameters) # 將準備好的 search_parameter 提供給 OR Tools 求解\n",
    "    if solution: # 有找到解的話顯示答案\n",
    "        routes = get_routes(solution, routing, manager)\n",
    "        print(f'Routes: {routes}, Length: {len(routes[0])}')\n",
    "        # print_solution(data, manager, routing, solution)\n",
    "        # 檢查路徑是否有跑完所有的點\n",
    "        serviced_node = sum([len(i) for i in routes]) - 1\n",
    "        if serviced_node != data[\"num_nodes\"]:\n",
    "            print(f'Warming: 僅訪問 {serviced_node} 個客戶點!')\n",
    "        return routes\n",
    "    else:\n",
    "        print('No solution!')\n",
    "        return []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [],
   "source": [
    "def select_drone_nodes(data, routes, excludes=[]):\n",
    "\n",
    "    # 找出最近距離 Node 排序\n",
    "    nearest_dists = []\n",
    "    for i in data['e_distance_matrix']:\n",
    "        sorted_i = sorted(i)\n",
    "        nearest_dists.append(sorted_i[1])\n",
    "    sorted_nearest_indexes = np.argsort(nearest_dists).tolist()[::-1]\n",
    "    sorted_nearest_indexes = sorted_nearest_indexes[:int(data[\"num_nodes\"])] \n",
    "    sorted_nearest_indexes.remove(0)\n",
    "\n",
    "    # 將 Node 分配到初始解車輛路徑中\n",
    "    drone_nodes = [[] for i in range(len(routes))]\n",
    "    for i, route in enumerate(routes):\n",
    "        for j in sorted_nearest_indexes:\n",
    "            drone_nodes[i].append(j) if j in route else None\n",
    "        drone_nodes[i] = drone_nodes[i][:int(len(route)/4)] # 根據中位數篩選出前 25% 最遠的點\n",
    "\n",
    "    # 如果有先解出 Robot 點, 需將 Robot 的收發站排除掉\n",
    "    if len(excludes) > 0:\n",
    "        for i, group in enumerate(excludes):\n",
    "            for j, nodes in enumerate(group):\n",
    "                for n in nodes:\n",
    "                    drone_nodes[i].remove(n) if n in drone_nodes[i] else None\n",
    "         \n",
    "    drone_routes = [[] for i in range(len(routes))]\n",
    "    for i, group in enumerate(drone_nodes):\n",
    "        exclusion = []\n",
    "        # 取得 Drone 的合適路徑\n",
    "        for n in group:\n",
    "            # 原路徑鄰的點不能為其他 Drone 點\n",
    "            if n not in exclusion:\n",
    "                start, end = routes[i].index(n)-1, routes[i].index(n)+1\n",
    "                exclusion.append(routes[i][start])\n",
    "                exclusion.append(routes[i][end])\n",
    "                route = [routes[i][start], n, routes[i][end]]\n",
    "                drone_routes[i].append(route)\n",
    "\n",
    "    # 排除不佳的路線: 會造成等待的 or 超過電池容量\n",
    "    for i, group in enumerate(drone_routes):\n",
    "        for r in group:\n",
    "            dur_d = get_objective_value(data, r, DRONE_SPEED, 'e_distance_matrix')\n",
    "            if dur_d > DRONE_BATTERY_LIFE: # 超過電池續航力\n",
    "                drone_routes[i].remove(r)\n",
    "                continue\n",
    "            start, end = r[0], r[-1]\n",
    "            r_v = routes[i][routes[i].index(start):routes[i].index(end)+1]\n",
    "            dur_v = get_objective_value(data, r_v, VEHICLE_SPEED)      \n",
    "            if dur_d + 2 >= dur_v: # Drone 較晚到達會產生等待 & 多花 2min 派遣 Drone 不如自己去跑\n",
    "                # print('Remove:', r)\n",
    "                drone_routes[i].remove(r)\n",
    "\n",
    "    return drone_routes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "metadata": {},
   "outputs": [],
   "source": [
    "def select_robot_nodes(data, routes):\n",
    "\n",
    "    robot_routes = [[] for i in range(len(routes))]\n",
    "    \n",
    "    for index, route in enumerate(routes):\n",
    "        # print('Choosing the nodes for Robot:', route)\n",
    "        if len(route) <= ROBOT_CAPACITIES + 2:\n",
    "            continue\n",
    "        route_filter = []\n",
    "        for j in range(len(route)):\n",
    "            if j <= (len(route) - ROBOT_CAPACITIES - 2):\n",
    "                robot_route = route[j:j + ROBOT_CAPACITIES + 2]            \n",
    "                r_dur = get_objective_value(data, robot_route, ROBOT_SPEED)\n",
    "                if r_dur <= ROBOT_BATTERY_LIFE: # 排除超過電池續航力(ROBOT_BATTERY_LIFE)的路徑組合\n",
    "                    # print(f'Route {j}: {robot_route}, Duratoin: {r_dur}')\n",
    "                    route_filter.append({ 'route': robot_route, 'duration': r_dur }) \n",
    "        # 根據最短時間(duration)排序, 並排除掉重複 Node 的路徑組合\n",
    "        route_filter.sort(key=lambda x: x['duration'])\n",
    "        if len(route_filter) >= ROBOT_CAPACITIES:\n",
    "            route_filter = route_filter[:int(len(route_filter)/4)] # 保留 25% 路徑組合\n",
    "        best_routes = [route_filter[0]['route']]\n",
    "        # print(best_routes)\n",
    "        for r_dict in route_filter:\n",
    "            overlap = 0\n",
    "            for best_r in best_routes:\n",
    "                if len(set(best_r) & set(r_dict['route'])) > 0:\n",
    "                    overlap += 1\n",
    "                    break\n",
    "            if overlap == 0:\n",
    "                best_routes.append(r_dict['route'])\n",
    "        robot_routes[index] = best_routes\n",
    "    # 每台車只會派出 Robot 一次\n",
    "    # robot_routes = [[robot_routes[i][0]] for i in range(len(routes))]\n",
    "    print('Robot Routes:', robot_routes)\n",
    "    return robot_routes\n",
    "\n",
    "def adjust_robot_route(data, route, robot_group):\n",
    "    print(f\"Route: {route}, Robot Group: {robot_group}\")\n",
    "    a_route = route.copy()\n",
    "    a_robot_group = robot_group.copy()\n",
    "\n",
    "    for index, route_r in enumerate(robot_group):\n",
    "        route_t = [route_r[0], route_r[-1]]\n",
    "        dur_r = get_objective_value(data, route_r, ROBOT_SPEED)\n",
    "        dur_t = get_objective_value(data, route_t)\n",
    "        if dur_r > dur_t:\n",
    "            # 1. forward stepwise search\n",
    "            route_f = route[route.index(route_t[-1])+1:] if route_t[-1] != 0 else [0] # 取得 Truck 接下來的路線\n",
    "            # exclude other dispatch nodes\n",
    "            for i in a_robot_group:\n",
    "                if i[0] in route_f:\n",
    "                    route_f = route_f[:route_f.index(i[0]) + 1] # 排除其他 Truck 的路線\n",
    "            # (Old) Truck 先去跑其他路徑, 時間差不多後再返回. 較沒有效率\n",
    "            # select the best route\n",
    "            # diff_abs = [abs(get_objective_value(data, [route_t[0]] + route_f[:i] + [route_t[-1]]) - dur_r) for i in range(len(route_f))]\n",
    "            # new_route = [route_t[0]] + route_f[:diff_abs.index(min(diff_abs))] + [route_t[-1]]\n",
    "            # (New) Robot 結束後到最近的點與 Truck 會合\n",
    "            trigger_f = 0 # 是否有更佳解的觸發器\n",
    "            diff_abs_f = []\n",
    "            diff_abs_f.append(abs(dur_r-dur_t)) # 如果沒有更好解時, 有可能保留原始解\n",
    "            for i, ele in enumerate(route_f):\n",
    "                route_fr = route_r[:-1] + [ele]\n",
    "                route_ft = route_t + route_f[:i+1]\n",
    "                dur_fr = get_objective_value(data, route_fr, ROBOT_SPEED)\n",
    "                if dur_fr > ROBOT_BATTERY_LIFE: # 超出電池續航力\n",
    "                    continue\n",
    "                dur_ft = get_objective_value(data, route_ft)\n",
    "                diff_abs_f.append(abs(dur_fr-dur_ft))\n",
    "                # 找到不用等待的解, 更新路徑\n",
    "                if dur_fr < dur_ft:\n",
    "                    new_route = route_ft\n",
    "                    a_robot_group[index] = route_fr\n",
    "                    trigger_f += 1\n",
    "                    break\n",
    "            # 如果 forward 後所有的解都要等待, 找出相對好的解\n",
    "            if trigger_f == 0:\n",
    "                best_i = diff_abs_f.index(min(diff_abs_f))\n",
    "                if best_i != 0: # 新路線比較好\n",
    "                    a_robot_group[index] = route_r[:-1] + [route_f[best_i - 1]]\n",
    "                    new_route = route_t + route_f[:best_i]\n",
    "                    dur_fr = get_objective_value(data, route_r[:-1] + [route_f[best_i - 1]], ROBOT_SPEED)   \n",
    "                else: # 原路線比較好\n",
    "                    new_route = route_t\n",
    "                    dur_fr = dur_r\n",
    "            # 2. backward stepwise search (if truck still needs waiting)\n",
    "            dur_ft = get_objective_value(data, new_route)\n",
    "            if dur_fr > dur_ft:\n",
    "                trigger_b = 0\n",
    "                diff_abs_b = []\n",
    "                diff_abs_b.append(abs(dur_fr - dur_ft))\n",
    "                # print(\"-Current waiting time:\", dur_r - get_objective_value(data, new_route))\n",
    "                route_b = route[:route.index(route_t[-1])]\n",
    "                # exclude other recall nodes\n",
    "                for i in a_robot_group:\n",
    "                    if i[-1] in route_b:\n",
    "                        route_b = route_b[route_b.index(i[-1]):]                \n",
    "                # select the best route\n",
    "                for i in range(2 ,len(route_b)):\n",
    "                    start = route_b[-i]\n",
    "                    route_br = [start] + route_r[1:]\n",
    "                    route_bt = a_route[a_route.index(start):a_route.index(route_r[0])] + new_route\n",
    "                    dur_br = get_objective_value(data, route_br, ROBOT_SPEED)\n",
    "                    dur_bt = get_objective_value(data, route_bt)\n",
    "                    # print(\"--Waiting time:\", dur_br - dur_bt)\n",
    "                    if dur_bt > dur_br:\n",
    "                        new_route = route_bt\n",
    "                        a_robot_group[index] = route_br\n",
    "                        trigger_b += 1\n",
    "                        break\n",
    "                # 如果 backward 後所有的解都要等待, 找出相對好的解\n",
    "                if trigger_b == 0:\n",
    "                    best_i = diff_abs_b.index(min(diff_abs_b))\n",
    "                    if best_i != 0: # 新路線比較好\n",
    "                        print('Find the better robot route by backward search')\n",
    "                        a_robot_group[index] = route_b[-best_i] + a_robot_group[index][1:]       \n",
    "            # print('Origin:', a_route[a_route.index(new_route[0]):a_route.index(new_route[0]) + len(new_route)])\n",
    "            # print('New:', new_route)\n",
    "            a_route[a_route.index(new_route[0]):a_route.index(new_route[0]) + len(new_route)] = new_route\n",
    "\n",
    "    # print(f\"Adjusted Truck Route: {a_route}\")\n",
    "    # print(f\"Adjusted Robot Route: {a_robot_group}\")\n",
    "\n",
    "    return a_route, a_robot_group"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## View: 畫面顯示"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_map(routes, drone_routes=[], robot_routes=[], **controls):\n",
    "    plt.figure(figsize=(7, 7))\n",
    "    plt.grid(color='gray', linestyle='-', linewidth=1, alpha=0.2)\n",
    "    plt.xlim(-1, controls[\"map_size\"][0]+1)\n",
    "    plt.ylim(-1, controls[\"map_size\"][1]+1) \n",
    "    plt.xlabel('x (km)')\n",
    "    plt.ylabel('y (km)')\n",
    "    color_palette = [(0, 0.5, 1), (0.8, 0, 0), (0.0, 0.6, 0.2), (1, 0.7, 0.4)]\n",
    "    passed_nodes = []\n",
    "\n",
    "    def draw_line(route, color='gray'):\n",
    "        arrow_kwargs = dict(length_includes_head=True, head_width=0.15, head_length=0.3, color=color, alpha=0.8)\n",
    "        for index, node in enumerate(route):\n",
    "            if index < len(route) - 1:\n",
    "                start_loc = data['num_locations'][route[index]]\n",
    "                end_loc = data['num_locations'][route[index + 1]] \n",
    "                plt.arrow(x=start_loc[0], y=start_loc[1], dx=(end_loc[0] - start_loc[0]), dy=(end_loc[1] - start_loc[1]), **arrow_kwargs)\n",
    "    \n",
    "    def draw_node(node, color='gray', marker='o', label='node'):\n",
    "        text_kwargs = dict(s=str(node), fontsize=7.5, color=\"white\", horizontalalignment='center', verticalalignment='center')\n",
    "        node_kwargs = dict(s=150, color=color, alpha=0.8, edgecolors='black', marker=marker, label=label)\n",
    "        loc = data['num_locations'][node]\n",
    "        plt.scatter(x=loc[0], y=loc[1], **node_kwargs)\n",
    "        # plt.text(x=loc[0], y=loc[1], **text_kwargs)\n",
    "        passed_nodes.append(node)\n",
    "\n",
    "    if len(routes) > 0:\n",
    "        # Draw VRP solution\n",
    "        for i_route, route in enumerate(routes):\n",
    "            RGB_color = color_palette[i_route]\n",
    "            draw_line(route, RGB_color)\n",
    "            # Draw vehicle nodes\n",
    "            for i in route:\n",
    "                if i != 0:\n",
    "                    draw_node(node=i, color=RGB_color)\n",
    "            # Draw drone nodes\n",
    "            if len(drone_routes) > 0:\n",
    "                for route in drone_routes[i_route]:\n",
    "                    drone_color = 'gray'\n",
    "                    for index, node in enumerate(route):\n",
    "                        if index != (len(route) - 1):\n",
    "                            draw_line(route, color=drone_color)\n",
    "                        if index == 1:\n",
    "                            draw_node(node, color=drone_color, marker='D', label='drone')         \n",
    "            # Draw robot nodes\n",
    "            if len(robot_routes) > 0:\n",
    "                for route in robot_routes[i_route]:\n",
    "                    robot_color = 'gray'\n",
    "                    for index, node in enumerate(route):\n",
    "                        if index != (len(route) - 1):\n",
    "                            draw_line(route)\n",
    "                        if 0 < index < (len(route) - 1):\n",
    "                            draw_node(node, color=robot_color, marker='H', label='robot')\n",
    "        # Draw un-passed nodes    \n",
    "        unpassed_nodes = [i for i in range(data[\"num_nodes\"]) if i not in passed_nodes]\n",
    "        if len(unpassed_nodes) > 0:\n",
    "            for index in unpassed_nodes:\n",
    "                draw_node(index)\n",
    "        # Draw depot\n",
    "        draw_node(node=0, color='black', marker='s') \n",
    "    # No route, plot map & nodes\n",
    "    else:\n",
    "        if len(data['num_locations']) > 0:\n",
    "            for index, node in enumerate(data['num_locations']):\n",
    "                draw_node(index) # depot\n",
    "            draw_node(node=0, color='black', marker='s', label='depot')\n",
    "        else:\n",
    "            print(\"No data.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## VRP 解題方法說明"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 223,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>num_locations</th>\n",
       "      <th>distance_matrix</th>\n",
       "      <th>e_distance_matrix</th>\n",
       "      <th>time_matrix</th>\n",
       "      <th>num_nodes</th>\n",
       "      <th>num_vehicles</th>\n",
       "      <th>depot</th>\n",
       "      <th>time_windows</th>\n",
       "      <th>initial_routes</th>\n",
       "      <th>demands</th>\n",
       "      <th>vehicle_capacities</th>\n",
       "      <th>vehicle</th>\n",
       "      <th>drone</th>\n",
       "      <th>robot</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>[(12.5, 12.5), (15.069, 13.622), (10.591, 16.1...</td>\n",
       "      <td>[[0, 3691, 5555, 11354, 14505, 8014, 12341, 21...</td>\n",
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       "      <td>110</td>\n",
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       "      <td>[110]</td>\n",
       "      <td>[]</td>\n",
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      ],
      "text/plain": [
       "                                       num_locations  \\\n",
       "0  [(12.5, 12.5), (15.069, 13.622), (10.591, 16.1...   \n",
       "\n",
       "                                     distance_matrix  \\\n",
       "0  [[0, 3691, 5555, 11354, 14505, 8014, 12341, 21...   \n",
       "\n",
       "                                   e_distance_matrix  \\\n",
       "0  [[0, 2803, 4116, 9917, 11952, 7328, 10775, 148...   \n",
       "\n",
       "                                         time_matrix  num_nodes  num_vehicles  \\\n",
       "0  [[0.0, 3.691, 5.555, 11.354, 14.505, 8.014, 12...        110             1   \n",
       "\n",
       "   depot time_windows initial_routes  \\\n",
       "0      0           []             []   \n",
       "\n",
       "                                             demands vehicle_capacities  \\\n",
       "0  [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...              [110]   \n",
       "\n",
       "  vehicle drone robot  \n",
       "0      []    []    []  "
      ]
     },
     "execution_count": 223,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 700x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Set data & control parameter\n",
    "controls = dict(map_size=(25, 25), num_nodes=110, num_vehicles=1)\n",
    "np.random.seed(0)\n",
    "data = create_data_model(**controls)\n",
    "\n",
    "plot_map(routes=[], **controls)\n",
    "\n",
    "pd.json_normalize(data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### VRP"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Routes: [[0, 82, 76, 51, 88, 48, 37, 103, 36, 93, 17, 61, 92, 4, 100, 64, 3, 97, 18, 49, 59, 16, 39, 9, 75, 53, 91, 99, 31, 11, 90, 23, 69, 62, 43, 63, 15, 109, 89, 79, 77, 5, 32, 68, 74, 41, 50, 70, 22, 25, 29, 34, 58, 10, 30, 2, 38, 80, 66, 21, 44, 42, 45, 87, 35, 20, 95, 73, 98, 47, 6, 106, 12, 83, 94, 102, 71, 108, 60, 81, 8, 57, 55, 104, 107, 33, 1, 65, 52, 86, 7, 67, 101, 19, 24, 26, 14, 72, 46, 27, 40, 13, 85, 54, 84, 28, 78, 96, 56, 105, 0]], Length: 111\n",
      "Vehicle 0: 240263 m, 460.263 min, including 0 mins waiting time.\n",
      "Total distance of all routes: : 240263 m\n",
      "Maximum travel time: 460.263 min\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "VRP_routes = solve_routing_problem(data)\n",
    "total_dist, total_time, waiting_time = get_travelling_time(data, VRP_routes)\n",
    "plot_map(routes=VRP_routes, **controls)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### VRP + Drone"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Routes: [[0, 14, 25, 65, 1, 53, 93, 67, 68, 18, 22, 72, 59, 19, 61, 92, 58, 78, 5, 97, 60, 80, 103, 69, 57, 94, 56, 64, 50, 106, 28, 91, 42, 29, 95, 101, 47, 39, 38, 23, 27, 30, 7, 102, 86, 79, 43, 85, 48, 89, 37, 21, 31, 84, 87, 33, 49, 34, 26, 105, 70, 4, 35, 36, 10, 82, 9, 51, 74, 81, 109, 44, 6, 104, 11, 55, 3, 71, 88, 54, 96, 13, 73, 75, 77, 8, 107, 41, 46, 12, 90, 76, 17, 99, 83, 63, 66, 98, 32, 24, 108, 40, 20, 52, 15, 100, 45, 2, 62, 16, 0]], Length: 111\n",
      "Waiting time: [[0, 0, 0, 0, 1.841, 4.011, 1.396, 0, 0, 0.226, 0.839, 0.576, 0, 0, 0, 0, 1.131]]\n",
      "Vehicle 0: 238613 m, 434.633 min, including 10.02 mins waiting time.\n",
      "Total distance of all routes: : 238613 m\n",
      "Maximum travel time: 434.633 min\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 解 VRP -> 分開挑選 Drone 點 -> 連接路線\n",
    "np.random.seed(0)\n",
    "data = create_data_model(**controls)\n",
    "VRPD_routes = solve_routing_problem(data)\n",
    "drone_routes = select_drone_nodes(data, VRPD_routes)\n",
    "# 調整車輛路線\n",
    "for index, group in enumerate(drone_routes):\n",
    "    for r in group:\n",
    "        VRPD_routes[index].remove(r[1])\n",
    "\n",
    "drone_waiting = get_waiting_time(data, VRPD_routes, drone_routes, 'drone')\n",
    "print(\"Waiting time:\", drone_waiting)\n",
    "total_dist, total_time, waiting_time = get_travelling_time(data, VRPD_routes, drone_waiting)\n",
    "\n",
    "plot_map(routes=VRPD_routes, drone_routes=drone_routes, robot_routes=[], **controls)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### VRP + Robot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Routes: [[0, 38, 62, 10, 51, 29, 2, 15, 76, 59, 79, 65, 97, 17, 107, 74, 45, 56, 5, 26, 60, 68, 106, 7, 36, 12, 83, 57, 64, 96, 77, 53, 54, 6, 67, 4, 20, 88, 25, 61, 14, 78, 72, 39, 23, 102, 43, 47, 33, 93, 69, 86, 16, 27, 80, 9, 28, 11, 44, 32, 52, 101, 103, 13, 90, 19, 98, 109, 92, 73, 91, 75, 70, 21, 104, 85, 66, 108, 18, 34, 84, 8, 48, 87, 22, 81, 94, 63, 35, 37, 42, 1, 46, 24, 40, 89, 105, 55, 50, 95, 100, 49, 41, 99, 31, 58, 71, 3, 82, 30, 0]], Length: 111\n",
      "Robot Routes: [[[87, 22, 81, 94, 63, 35, 37, 42, 1, 46, 24, 40], [76, 59, 79, 65, 97, 17, 107, 74, 45, 56, 5, 26], [101, 103, 13, 90, 19, 98, 109, 92, 73, 91, 75, 70], [72, 39, 23, 102, 43, 47, 33, 93, 69, 86, 16, 27]]]\n",
      "Route: [0, 38, 62, 10, 51, 29, 2, 15, 76, 26, 60, 68, 106, 7, 36, 12, 83, 57, 64, 96, 77, 53, 54, 6, 67, 4, 20, 88, 25, 61, 14, 78, 72, 27, 80, 9, 28, 11, 44, 32, 52, 101, 70, 21, 104, 85, 66, 108, 18, 34, 84, 8, 48, 87, 40, 89, 105, 55, 50, 95, 100, 49, 41, 99, 31, 58, 71, 3, 82, 30, 0], Robot Group: [[87, 22, 81, 94, 63, 35, 37, 42, 1, 46, 24, 40], [76, 59, 79, 65, 97, 17, 107, 74, 45, 56, 5, 26], [101, 103, 13, 90, 19, 98, 109, 92, 73, 91, 75, 70], [72, 39, 23, 102, 43, 47, 33, 93, 69, 86, 16, 27]]\n",
      "Waiting time: [[0, 0, 0, 0]]\n",
      "Vehicle 0: 229039 m, 369.039 min, including 0 mins waiting time.\n",
      "Total distance of all routes: : 229039 m\n",
      "Maximum travel time: 369.039 min\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# np.random.seed(0)\n",
    "data = create_data_model(**controls)\n",
    "VRPR_routes = solve_routing_problem(data)\n",
    "robot_routes = select_robot_nodes(data, VRPR_routes)\n",
    "# 調整車輛路線\n",
    "for veh_i, group in enumerate(robot_routes):\n",
    "    for index, route in enumerate(group):\n",
    "        exclude_nodes = [item for sublist in robot_routes[veh_i] for item in sublist if 0 < sublist.index(item) < len(sublist) - 1]\n",
    "        VRPR_routes[veh_i] = [i for i in VRPR_routes[veh_i] if i not in exclude_nodes]   \n",
    "    VRPR_routes[veh_i], robot_routes[veh_i] = adjust_robot_route(data, VRPR_routes[veh_i], group)\n",
    "\n",
    "robot_waiting = get_waiting_time(data, VRPR_routes, robot_routes, 'robot')\n",
    "print(\"Waiting time:\", robot_waiting)\n",
    "total_dist, total_time, waiting_time = get_travelling_time(data, VRPR_routes, [], robot_waiting)\n",
    "\n",
    "plot_map(routes=VRPR_routes, robot_routes=robot_routes, **controls)\n",
    "\n",
    "# 舊版方法 (VRPTW)\n",
    "# vrptw_routes = solve_vrptw(data, excludes)\n",
    "# print('\\nRoute for VRPTW:', vrptw_routes)\n",
    "# if vrptw_routes:\n",
    "#     robot_waiting = get_waiting_time(data, vrptw_routes, robot_routes, 'robot')\n",
    "# plot_map(routes=vrptw_routes, drone_routes=[], robot_routes=robot_routes, **controls)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### VRP + Drone + Robot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Routes: [[0, 14, 25, 65, 1, 53, 93, 67, 68, 18, 22, 72, 59, 19, 61, 92, 58, 78, 5, 97, 60, 80, 103, 69, 57, 94, 56, 64, 50, 106, 28, 91, 42, 29, 95, 101, 47, 39, 38, 23, 27, 30, 7, 102, 86, 79, 43, 85, 48, 89, 37, 21, 31, 84, 87, 33, 49, 34, 26, 105, 70, 4, 35, 36, 10, 82, 9, 51, 74, 81, 109, 44, 6, 104, 11, 55, 3, 71, 88, 54, 96, 13, 73, 75, 77, 8, 107, 41, 46, 12, 90, 76, 17, 99, 83, 63, 66, 98, 32, 24, 108, 40, 20, 52, 15, 100, 45, 2, 62, 16, 0]], Length: 111\n",
      "Robot Routes: [[[64, 50, 106, 28, 91, 42, 29, 95, 101, 47, 39, 38], [59, 19, 61, 92, 58, 78, 5, 97, 60, 80, 103, 69], [96, 13, 73, 75, 77, 8, 107, 41, 46, 12, 90, 76]]]\n",
      "Route: [0, 14, 25, 65, 1, 53, 93, 67, 68, 18, 22, 72, 59, 69, 57, 94, 56, 64, 38, 23, 27, 30, 7, 102, 86, 79, 43, 85, 48, 89, 37, 21, 31, 84, 87, 33, 49, 34, 26, 105, 70, 4, 35, 36, 10, 82, 9, 51, 74, 81, 109, 44, 6, 104, 11, 55, 3, 71, 88, 54, 96, 76, 17, 99, 83, 63, 66, 98, 32, 24, 108, 40, 20, 52, 15, 100, 45, 2, 62, 16, 0], Robot Group: [[64, 50, 106, 28, 91, 42, 29, 95, 101, 47, 39, 38], [59, 19, 61, 92, 58, 78, 5, 97, 60, 80, 103, 69], [96, 13, 73, 75, 77, 8, 107, 41, 46, 12, 90, 76]]\n",
      "[0, 14, 25, 65, 1, 53, 93, 67, 68, 18, 22, 72, 59, 69, 57, 94, 56, 64, 38, 23, 27, 30, 7, 102, 86, 79, 43, 85, 48, 89, 37, 21, 31, 84, 87, 33, 49, 34, 26, 105, 70, 4, 35, 36, 10, 82, 9, 51, 74, 81, 109, 44, 6, 104, 11, 55, 3, 71, 88, 54, 96, 76, 17, 99, 83, 63, 66, 98, 32, 24, 108, 40, 20, 52, 15, 100, 45, 2, 62, 16, 0] [[64, 50, 106, 28, 91, 42, 29, 95, 101, 47, 39, 79], [22, 19, 61, 92, 58, 78, 5, 97, 60, 80, 103, 69], [96, 13, 73, 75, 77, 8, 107, 41, 46, 12, 90, 108]]\n",
      "Waiting time(d): [[0, 0, 0, 0, 1.841, 4.011, 1.396, 0, 0, 0.226, 0.839, 0.576]]\n",
      "Waiting time(r): [[0, 19.162, 5.302]]\n",
      "Vehicle 0: 219980 m, 389.333 min, including 33.353 mins waiting time.\n",
      "Total distance of all routes: : 219980 m\n",
      "Maximum travel time: 389.333 min\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "np.random.seed(0)\n",
    "data = create_data_model(**controls)\n",
    "VRPRD_routes = solve_routing_problem(data)\n",
    "\n",
    "robot_routes = select_robot_nodes(data, VRPRD_routes)\n",
    "\n",
    "for veh_i, group in enumerate(robot_routes):\n",
    "    for index, route in enumerate(group):\n",
    "        exclude_nodes = [item for sublist in robot_routes[veh_i] for item in sublist if 0 < sublist.index(item) < len(sublist) - 1]\n",
    "        VRPRD_routes[veh_i] = [i for i in VRPRD_routes[veh_i] if i not in exclude_nodes]   \n",
    "    VRPRD_routes[veh_i], robot_routes[veh_i] = adjust_robot_route(data, VRPRD_routes[veh_i], group)\n",
    "    print(VRPRD_routes[veh_i], robot_routes[veh_i])\n",
    "\n",
    "drone_routes = select_drone_nodes(data, VRPRD_routes, excludes=robot_routes)\n",
    "\n",
    "for index, group in enumerate(drone_routes):\n",
    "    for r in group:\n",
    "        VRPRD_routes[index].remove(r[1])\n",
    "\n",
    "drone_waiting = get_waiting_time(data, VRPRD_routes, drone_routes, 'drone')\n",
    "robot_waiting = get_waiting_time(data, VRPRD_routes, robot_routes, 'robot')\n",
    "print(\"Waiting time(d):\", drone_waiting)\n",
    "print(\"Waiting time(r):\", robot_waiting)\n",
    "total_dist, total_time, waiting_time = get_travelling_time(data, VRPRD_routes, drone_waiting, robot_waiting)\n",
    "\n",
    "plot_map(routes=VRPRD_routes, drone_routes=drone_routes, robot_routes=robot_routes, **controls)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Main: 設定參數與記錄實驗結果"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {},
   "outputs": [],
   "source": [
    "def create_result_model():\n",
    "    \n",
    "    result = {}   \n",
    "    # Parameters\n",
    "    result[\"id\"] = []\n",
    "    result[\"map_size\"] = []\n",
    "    result[\"num_nodes\"] = []\n",
    "    result[\"num_locations\"] = []\n",
    "    result[\"num_vehicles\"] = []\n",
    "    result[\"vehicle_capacities\"] = []\n",
    "    # Result of VRP\n",
    "    result[\"type\"] = []\n",
    "    result[\"truck_routes\"] = []\n",
    "    result[\"drone_routes\"] = []\n",
    "    result[\"robot_routes\"] = []\n",
    "    result[\"distances\"] = []\n",
    "    result[\"time\"] = []\n",
    "    result[\"waiting\"] = []\n",
    "    result[\"dispatch\"] = []\n",
    "    result[\"total_distance\"] = []\n",
    "    result[\"travel_time\"] = []\n",
    "    result[\"time_complexity\"] = []\n",
    "    result[\"space_complexity\"] = []\n",
    "    return result\n",
    "\n",
    "def solve_by_VRP(data):\n",
    "    start_time = time.time()\n",
    "    tracemalloc.start()\n",
    "    '''algorithm starts'''\n",
    "    routes = solve_routing_problem(data)\n",
    "    total_dist, total_time, waiting_time = get_travelling_time(data, routes)\n",
    "    '''algorithm ends'''\n",
    "    end_time = time.time()\n",
    "    current, peak = tracemalloc.get_traced_memory()\n",
    "    tracemalloc.stop()\n",
    "    time_complexity = round(end_time - start_time, 4)\n",
    "    space_complexity = round(current / 1024, 4)\n",
    "    VRP_result = dict(type='VRP', truck_routes=routes,  drone_routes=np.nan, robot_routes=np.nan, distances=total_dist, time=total_time, waiting=np.nan, dispatch=np.nan, total_distance=np.sum(total_dist), travel_time=max(total_time), time_complexity=time_complexity, space_complexity=space_complexity)\n",
    "    return VRP_result\n",
    "\n",
    "def solve_by_VRPD(data):\n",
    "    start_time = time.time()\n",
    "    tracemalloc.start()\n",
    "    '''algorithm starts'''\n",
    "    routes = solve_routing_problem(data)\n",
    "    drone_routes = select_drone_nodes(data, routes)\n",
    "    for index, group in enumerate(drone_routes):\n",
    "        for r in group:\n",
    "            routes[index].remove(r[1])\n",
    "    drone_waiting = get_waiting_time(data, routes, drone_routes, 'drone')\n",
    "    robot_waiting = [[] for i in range(len(drone_waiting))]\n",
    "    total_dist, total_time, waiting_time = get_travelling_time(data, routes, drone_waiting, robot_waiting)\n",
    "    # 考量派遣時間\n",
    "    travel_time = total_time.copy()\n",
    "    drone_dispatch = get_dispatch_time(drone_routes)\n",
    "    for i, j in enumerate(drone_dispatch):\n",
    "        travel_time[i] += waiting_time[i]\n",
    "        travel_time[i] += j       \n",
    "    '''algorithm ends'''\n",
    "    end_time = time.time()\n",
    "    current, peak = tracemalloc.get_traced_memory()\n",
    "    tracemalloc.stop()\n",
    "    time_complexity = round(end_time - start_time, 4)\n",
    "    space_complexity = round(current / 1024, 4)\n",
    "    VRPD_result = dict(type='VRP-D', truck_routes=routes, drone_routes=drone_routes, robot_routes=np.nan, distances=total_dist, time=total_time, waiting=waiting_time, dispatch=drone_dispatch, total_distance=np.sum(total_dist), travel_time=max(total_time), time_complexity=time_complexity, space_complexity=space_complexity)\n",
    "    return VRPD_result\n",
    "\n",
    "def solve_by_VRPR(data):\n",
    "    start_time = time.time()\n",
    "    tracemalloc.start()\n",
    "    '''algorithm starts'''\n",
    "    routes = solve_routing_problem(data)\n",
    "    robot_routes = select_robot_nodes(data, routes)\n",
    "    for veh_i, group in enumerate(robot_routes):\n",
    "        for index, route in enumerate(group):\n",
    "            exclude_nodes = [item for sublist in robot_routes[veh_i] for item in sublist if 0 < sublist.index(item) < len(sublist) - 1]\n",
    "            routes[veh_i] = [i for i in routes[veh_i] if i not in exclude_nodes]   \n",
    "        routes[veh_i], robot_routes[veh_i] = adjust_robot_route(data, routes[veh_i], group)\n",
    "    robot_waiting = get_waiting_time(data, routes, robot_routes, 'robot')\n",
    "    drone_waiting = [[] for i in range(len(robot_waiting))]\n",
    "    total_dist, total_time, waiting_time = get_travelling_time(data, routes, drone_waiting, robot_waiting)  \n",
    "    # 考量派遣時間\n",
    "    robot_dispatch = get_dispatch_time(robot_routes)\n",
    "    for i, j in enumerate(robot_dispatch):\n",
    "        total_time[i] += j        \n",
    "    '''algorithm ends'''\n",
    "    end_time = time.time()\n",
    "    current, peak = tracemalloc.get_traced_memory()\n",
    "    tracemalloc.stop()\n",
    "    time_complexity = round(end_time - start_time, 4)\n",
    "    space_complexity = round(current / 1024, 4)\n",
    "    VRPR_result = dict(type='VRP-R', truck_routes=routes,  drone_routes=np.nan, robot_routes=robot_routes, distances=total_dist, time=total_time, waiting=waiting_time, dispatch=robot_dispatch, total_distance=np.sum(total_dist), travel_time=max(total_time), time_complexity=time_complexity, space_complexity=space_complexity)\n",
    "    return VRPR_result\n",
    "\n",
    "def solve_by_VRPRD(data):\n",
    "    start_time = time.time()\n",
    "    tracemalloc.start()\n",
    "    '''algorithm starts'''\n",
    "    routes = solve_routing_problem(data)\n",
    "    robot_routes = select_robot_nodes(data, routes)\n",
    "    for veh_i, group in enumerate(robot_routes):\n",
    "        for index, route in enumerate(group):\n",
    "            exclude_nodes = [item for sublist in robot_routes[veh_i] for item in sublist if 0 < sublist.index(item) < len(sublist) - 1]\n",
    "            routes[veh_i] = [i for i in routes[veh_i] if i not in exclude_nodes]   \n",
    "        routes[veh_i], robot_routes[veh_i] = adjust_robot_route(data, routes[veh_i], group)\n",
    "    drone_routes = select_drone_nodes(data, routes, excludes=robot_routes)\n",
    "    for index, group in enumerate(drone_routes):\n",
    "        for r in group:\n",
    "            routes[index].remove(r[1])\n",
    "    drone_waiting = get_waiting_time(data, routes, drone_routes, 'drone')\n",
    "    robot_waiting = get_waiting_time(data, routes, robot_routes, 'robot')\n",
    "    total_dist, total_time, waiting_time = get_travelling_time(data, routes, drone_waiting, robot_waiting)  \n",
    "    # 考量派遣時間\n",
    "    drone_dispatch = get_dispatch_time(drone_routes)\n",
    "    robot_dispatch = get_dispatch_time(robot_routes)\n",
    "    dispatch_time = [drone_dispatch[i]+robot_dispatch[i] for i in range(len(drone_dispatch))]\n",
    "    for i, j in enumerate(zip(drone_dispatch, robot_dispatch)):\n",
    "        total_time[i] += (j[0] + j[1])\n",
    "    '''algorithm ends'''\n",
    "    end_time = time.time()\n",
    "    current, peak = tracemalloc.get_traced_memory()\n",
    "    tracemalloc.stop()\n",
    "    time_complexity = round(end_time - start_time, 4)\n",
    "    space_complexity = round(current / 1024, 4)\n",
    "    VRPRD_result = dict(type='VRP-RD', truck_routes=routes, drone_routes=drone_routes, robot_routes=robot_routes, distances=total_dist, time=total_time, waiting=waiting_time, dispatch=dispatch_time, total_distance=np.sum(total_dist), travel_time=max(total_time), time_complexity=time_complexity, space_complexity=space_complexity)\n",
    "    return VRPRD_result\n",
    "\n",
    "def save_exp_parameter(iter, data, **controls):\n",
    "    result[\"id\"].append(iter)\n",
    "    result[\"map_size\"].append((controls[\"map_size\"][0], controls[\"map_size\"][1]))\n",
    "    result[\"num_nodes\"].append(data[\"num_nodes\"])\n",
    "    result[\"num_locations\"].append(data[\"num_locations\"])\n",
    "    result[\"num_vehicles\"].append(controls[\"num_vehicles\"])\n",
    "    result[\"vehicle_capacities\"].append(data[\"vehicle_capacities\"])\n",
    "\n",
    "# 地圖大小, 客戶點數量, 車輛數, 模擬次數\n",
    "def simulate_experiment(**controls):\n",
    "\n",
    "    for iter in range(1, controls[\"trials\"]+1):\n",
    "        print(f'Trial {iter}...')\n",
    "        data = create_data_model(**controls)\n",
    "        # 解 VRP & 記錄結果\n",
    "        try:\n",
    "            print('VRP')\n",
    "            VRP_result = solve_by_VRP(data)\n",
    "            save_exp_parameter(iter, data, **controls)\n",
    "            for key, value in VRP_result.items():\n",
    "                if key in result:\n",
    "                    result[key].append(value)\n",
    "        except:\n",
    "            print('VRP Error!')\n",
    "        # 解 VRP-D & 記錄結果\n",
    "        try:\n",
    "            print('VRP-D')\n",
    "            VRPD_result = solve_by_VRPD(data)\n",
    "            save_exp_parameter(iter, data, **controls)\n",
    "            for key, value in VRPD_result.items():\n",
    "                if key in result:\n",
    "                    result[key].append(value)\n",
    "        except:\n",
    "            print('VRP-D Error!')\n",
    "        # 解 VRP-R & 記錄結果\n",
    "        try:\n",
    "            print('VRP-R')\n",
    "            VRPR_result = solve_by_VRPR(data)\n",
    "            save_exp_parameter(iter, data, **controls)\n",
    "            for key, value in VRPR_result.items():\n",
    "                if key in result:\n",
    "                    result[key].append(value)\n",
    "        except: \n",
    "            print('VRP-R Error!')\n",
    "        # 解 VRP-RD & 記錄結果\n",
    "        try:\n",
    "            print('VRP-RD')\n",
    "            VRPRD_result = solve_by_VRPRD(data)\n",
    "            save_exp_parameter(iter, data, **controls)\n",
    "            for key, value in VRPRD_result.items():\n",
    "                if key in result:\n",
    "                    result[key].append(value)\n",
    "        except:\n",
    "            print('VRP-RD Error!')\n",
    "\n",
    "    print('\\nDone!')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 執行實驗"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Trial 1...\n",
      "VRP\n",
      "Routes: [[0, 22, 192, 10, 66, 161, 186, 136, 149, 141, 154, 106, 29, 79, 63, 68, 81, 109, 89, 32, 64, 127, 135, 99, 131, 60, 162, 65, 171, 150, 14, 59, 40, 132, 34, 191, 121, 111, 187, 71, 170, 20, 91, 95, 193, 144, 200, 45, 156, 172, 126, 46, 157, 18, 17, 202, 31, 147, 116, 208, 142, 75, 104, 182, 114, 86, 92, 96, 155, 9, 85, 15, 148, 38, 179, 160, 112, 201, 102, 13, 204, 105, 39, 88, 195, 133, 61, 7, 56, 167, 125, 28, 44, 177, 108, 118, 100, 137, 69, 120, 50, 37, 77, 180, 199, 145, 181, 1, 153, 84, 83, 78, 169, 52, 178, 152, 98, 72, 174, 49, 80, 196, 19, 58, 41, 134, 188, 123, 82, 205, 30, 119, 194, 12, 107, 158, 2, 138, 203, 93, 8, 165, 146, 113, 197, 168, 67, 11, 103, 35, 163, 62, 159, 129, 42, 57, 54, 101, 117, 74, 151, 128, 175, 55, 206, 16, 183, 130, 185, 198, 143, 4, 209, 189, 6, 207, 26, 76, 87, 110, 124, 33, 190, 164, 47, 122, 27, 140, 90, 24, 139, 51, 43, 176, 166, 48, 184, 21, 5, 36, 25, 97, 173, 115, 70, 3, 23, 53, 94, 73, 0]], Length: 211\n",
      "Vehicle 0: 71461 m, 491.461 min, including 0 mins waiting time.\n",
      "Total distance of all routes: : 71461 m\n",
      "Maximum travel time: 491.461 min\n",
      "VRP-D\n",
      "Routes: [[0, 22, 192, 10, 66, 161, 186, 136, 149, 141, 154, 106, 29, 79, 63, 68, 81, 109, 89, 32, 64, 127, 135, 99, 131, 60, 162, 65, 171, 150, 14, 59, 40, 132, 34, 191, 121, 111, 187, 71, 170, 20, 91, 95, 193, 144, 200, 45, 156, 172, 126, 46, 157, 18, 17, 202, 31, 147, 116, 208, 142, 75, 104, 182, 114, 86, 92, 96, 155, 9, 85, 15, 148, 38, 179, 160, 112, 201, 102, 13, 204, 105, 39, 88, 195, 133, 61, 7, 56, 167, 125, 28, 44, 177, 108, 118, 100, 137, 69, 120, 50, 37, 77, 180, 199, 145, 181, 1, 153, 84, 83, 78, 169, 52, 178, 152, 98, 72, 174, 49, 80, 196, 19, 58, 41, 134, 188, 123, 82, 205, 30, 119, 194, 12, 107, 158, 2, 138, 203, 93, 8, 165, 146, 113, 197, 168, 67, 11, 103, 35, 163, 62, 159, 129, 42, 57, 54, 101, 117, 74, 151, 128, 175, 55, 206, 16, 183, 130, 185, 198, 143, 4, 209, 189, 6, 207, 26, 76, 87, 110, 124, 33, 190, 164, 47, 122, 27, 140, 90, 24, 139, 51, 43, 176, 166, 48, 184, 21, 5, 36, 25, 97, 173, 115, 70, 3, 23, 53, 94, 73, 0]], Length: 211\n",
      "Vehicle 0: 66541 m, 468.401 min, including 15.86 mins waiting time.\n",
      "Total distance of all routes: : 66541 m\n",
      "Maximum travel time: 468.401 min\n",
      "VRP-R\n",
      "Routes: [[0, 22, 192, 10, 66, 161, 186, 136, 149, 141, 154, 106, 29, 79, 63, 68, 81, 109, 89, 32, 64, 127, 135, 99, 131, 60, 162, 65, 171, 150, 14, 59, 40, 132, 34, 191, 121, 111, 187, 71, 170, 20, 91, 95, 193, 144, 200, 45, 156, 172, 126, 46, 157, 18, 17, 202, 31, 147, 116, 208, 142, 75, 104, 182, 114, 86, 92, 96, 155, 9, 85, 15, 148, 38, 179, 160, 112, 201, 102, 13, 204, 105, 39, 88, 195, 133, 61, 7, 56, 167, 125, 28, 44, 177, 108, 118, 100, 137, 69, 120, 50, 37, 77, 180, 199, 145, 181, 1, 153, 84, 83, 78, 169, 52, 178, 152, 98, 72, 174, 49, 80, 196, 19, 58, 41, 134, 188, 123, 82, 205, 30, 119, 194, 12, 107, 158, 2, 138, 203, 93, 8, 165, 146, 113, 197, 168, 67, 11, 103, 35, 163, 62, 159, 129, 42, 57, 54, 101, 117, 74, 151, 128, 175, 55, 206, 16, 183, 130, 185, 198, 143, 4, 209, 189, 6, 207, 26, 76, 87, 110, 124, 33, 190, 164, 47, 122, 27, 140, 90, 24, 139, 51, 43, 176, 166, 48, 184, 21, 5, 36, 25, 97, 173, 115, 70, 3, 23, 53, 94, 73, 0]], Length: 211\n",
      "Robot Routes: [[[93, 8, 165, 146, 113, 197, 168, 67, 11, 103, 35, 163], [135, 99, 131, 60, 162, 65, 171, 150, 14, 59, 40, 132], [133, 61, 7, 56, 167, 125, 28, 44, 177, 108, 118, 100], [123, 82, 205, 30, 119, 194, 12, 107, 158, 2, 138, 203], [129, 42, 57, 54, 101, 117, 74, 151, 128, 175, 55, 206], [121, 111, 187, 71, 170, 20, 91, 95, 193, 144, 200, 45], [0, 22, 192, 10, 66, 161, 186, 136, 149, 141, 154, 106], [24, 139, 51, 43, 176, 166, 48, 184, 21, 5, 36, 25]]]\n",
      "Route: [0, 106, 29, 79, 63, 68, 81, 109, 89, 32, 64, 127, 135, 132, 34, 191, 121, 45, 156, 172, 126, 46, 157, 18, 17, 202, 31, 147, 116, 208, 142, 75, 104, 182, 114, 86, 92, 96, 155, 9, 85, 15, 148, 38, 179, 160, 112, 201, 102, 13, 204, 105, 39, 88, 195, 133, 100, 137, 69, 120, 50, 37, 77, 180, 199, 145, 181, 1, 153, 84, 83, 78, 169, 52, 178, 152, 98, 72, 174, 49, 80, 196, 19, 58, 41, 134, 188, 123, 203, 93, 163, 62, 159, 129, 206, 16, 183, 130, 185, 198, 143, 4, 209, 189, 6, 207, 26, 76, 87, 110, 124, 33, 190, 164, 47, 122, 27, 140, 90, 24, 25, 97, 173, 115, 70, 3, 23, 53, 94, 73, 0], Robot Group: [[93, 8, 165, 146, 113, 197, 168, 67, 11, 103, 35, 163], [135, 99, 131, 60, 162, 65, 171, 150, 14, 59, 40, 132], [133, 61, 7, 56, 167, 125, 28, 44, 177, 108, 118, 100], [123, 82, 205, 30, 119, 194, 12, 107, 158, 2, 138, 203], [129, 42, 57, 54, 101, 117, 74, 151, 128, 175, 55, 206], [121, 111, 187, 71, 170, 20, 91, 95, 193, 144, 200, 45], [0, 22, 192, 10, 66, 161, 186, 136, 149, 141, 154, 106], [24, 139, 51, 43, 176, 166, 48, 184, 21, 5, 36, 25]]\n",
      "Vehicle 0: 60636 m, 375.501 min, including 54.865 mins waiting time.\n",
      "Total distance of all routes: : 60636 m\n",
      "Maximum travel time: 375.501 min\n",
      "VRP-RD\n",
      "Routes: [[0, 22, 192, 10, 66, 161, 186, 136, 149, 141, 154, 106, 29, 79, 63, 68, 81, 109, 89, 32, 64, 127, 135, 99, 131, 60, 162, 65, 171, 150, 14, 59, 40, 132, 34, 191, 121, 111, 187, 71, 170, 20, 91, 95, 193, 144, 200, 45, 156, 172, 126, 46, 157, 18, 17, 202, 31, 147, 116, 208, 142, 75, 104, 182, 114, 86, 92, 96, 155, 9, 85, 15, 148, 38, 179, 160, 112, 201, 102, 13, 204, 105, 39, 88, 195, 133, 61, 7, 56, 167, 125, 28, 44, 177, 108, 118, 100, 137, 69, 120, 50, 37, 77, 180, 199, 145, 181, 1, 153, 84, 83, 78, 169, 52, 178, 152, 98, 72, 174, 49, 80, 196, 19, 58, 41, 134, 188, 123, 82, 205, 30, 119, 194, 12, 107, 158, 2, 138, 203, 93, 8, 165, 146, 113, 197, 168, 67, 11, 103, 35, 163, 62, 159, 129, 42, 57, 54, 101, 117, 74, 151, 128, 175, 55, 206, 16, 183, 130, 185, 198, 143, 4, 209, 189, 6, 207, 26, 76, 87, 110, 124, 33, 190, 164, 47, 122, 27, 140, 90, 24, 139, 51, 43, 176, 166, 48, 184, 21, 5, 36, 25, 97, 173, 115, 70, 3, 23, 53, 94, 73, 0]], Length: 211\n",
      "Robot Routes: [[[93, 8, 165, 146, 113, 197, 168, 67, 11, 103, 35, 163], [135, 99, 131, 60, 162, 65, 171, 150, 14, 59, 40, 132], [133, 61, 7, 56, 167, 125, 28, 44, 177, 108, 118, 100], [123, 82, 205, 30, 119, 194, 12, 107, 158, 2, 138, 203], [129, 42, 57, 54, 101, 117, 74, 151, 128, 175, 55, 206], [121, 111, 187, 71, 170, 20, 91, 95, 193, 144, 200, 45], [0, 22, 192, 10, 66, 161, 186, 136, 149, 141, 154, 106], [24, 139, 51, 43, 176, 166, 48, 184, 21, 5, 36, 25]]]\n",
      "Route: [0, 106, 29, 79, 63, 68, 81, 109, 89, 32, 64, 127, 135, 132, 34, 191, 121, 45, 156, 172, 126, 46, 157, 18, 17, 202, 31, 147, 116, 208, 142, 75, 104, 182, 114, 86, 92, 96, 155, 9, 85, 15, 148, 38, 179, 160, 112, 201, 102, 13, 204, 105, 39, 88, 195, 133, 100, 137, 69, 120, 50, 37, 77, 180, 199, 145, 181, 1, 153, 84, 83, 78, 169, 52, 178, 152, 98, 72, 174, 49, 80, 196, 19, 58, 41, 134, 188, 123, 203, 93, 163, 62, 159, 129, 206, 16, 183, 130, 185, 198, 143, 4, 209, 189, 6, 207, 26, 76, 87, 110, 124, 33, 190, 164, 47, 122, 27, 140, 90, 24, 25, 97, 173, 115, 70, 3, 23, 53, 94, 73, 0], Robot Group: [[93, 8, 165, 146, 113, 197, 168, 67, 11, 103, 35, 163], [135, 99, 131, 60, 162, 65, 171, 150, 14, 59, 40, 132], [133, 61, 7, 56, 167, 125, 28, 44, 177, 108, 118, 100], [123, 82, 205, 30, 119, 194, 12, 107, 158, 2, 138, 203], [129, 42, 57, 54, 101, 117, 74, 151, 128, 175, 55, 206], [121, 111, 187, 71, 170, 20, 91, 95, 193, 144, 200, 45], [0, 22, 192, 10, 66, 161, 186, 136, 149, 141, 154, 106], [24, 139, 51, 43, 176, 166, 48, 184, 21, 5, 36, 25]]\n",
      "Vehicle 0: 57243 m, 365.251 min, including 68.008 mins waiting time.\n",
      "Total distance of all routes: : 57243 m\n",
      "Maximum travel time: 365.251 min\n",
      "Trial 2...\n",
      "VRP\n",
      "Routes: [[0, 193, 95, 191, 53, 198, 167, 136, 88, 91, 19, 40, 127, 50, 116, 139, 7, 171, 29, 178, 145, 181, 54, 47, 20, 177, 37, 51, 80, 154, 186, 162, 62, 118, 42, 120, 112, 202, 32, 163, 64, 199, 200, 114, 27, 67, 174, 98, 43, 1, 195, 151, 160, 94, 170, 179, 48, 155, 68, 17, 83, 143, 9, 150, 165, 65, 187, 4, 106, 105, 61, 92, 189, 45, 18, 96, 125, 168, 123, 133, 84, 72, 131, 111, 60, 79, 97, 184, 44, 148, 109, 108, 86, 55, 101, 93, 176, 5, 82, 121, 6, 23, 185, 85, 102, 104, 142, 182, 58, 209, 12, 124, 172, 99, 90, 166, 130, 206, 128, 74, 113, 77, 36, 204, 146, 190, 135, 164, 59, 38, 208, 2, 107, 153, 28, 126, 183, 147, 138, 207, 30, 89, 152, 161, 78, 196, 144, 31, 22, 13, 203, 140, 129, 63, 100, 87, 70, 16, 159, 81, 156, 11, 76, 57, 8, 33, 3, 35, 75, 15, 194, 66, 52, 117, 149, 56, 41, 157, 141, 73, 49, 39, 158, 169, 71, 175, 122, 197, 34, 25, 115, 173, 14, 134, 201, 205, 26, 192, 188, 119, 110, 137, 69, 180, 46, 21, 24, 103, 10, 132, 0]], Length: 211\n",
      "Vehicle 0: 70735 m, 490.735 min, including 0 mins waiting time.\n",
      "Total distance of all routes: : 70735 m\n",
      "Maximum travel time: 490.735 min\n",
      "VRP-D\n",
      "Routes: [[0, 193, 95, 191, 53, 198, 167, 136, 88, 91, 19, 40, 127, 50, 116, 139, 7, 171, 29, 178, 145, 181, 54, 47, 20, 177, 37, 51, 80, 154, 186, 162, 62, 118, 42, 120, 112, 202, 32, 163, 64, 199, 200, 114, 27, 67, 174, 98, 43, 1, 195, 151, 160, 94, 170, 179, 48, 155, 68, 17, 83, 143, 9, 150, 165, 65, 187, 4, 106, 105, 61, 92, 189, 45, 18, 96, 125, 168, 123, 133, 84, 72, 131, 111, 60, 79, 97, 184, 44, 148, 109, 108, 86, 55, 101, 93, 176, 5, 82, 121, 6, 23, 185, 85, 102, 104, 142, 182, 58, 209, 12, 124, 172, 99, 90, 166, 130, 206, 128, 74, 113, 77, 36, 204, 146, 190, 135, 164, 59, 38, 208, 2, 107, 153, 28, 126, 183, 147, 138, 207, 30, 89, 152, 161, 78, 196, 144, 31, 22, 13, 203, 140, 129, 63, 100, 87, 70, 16, 159, 81, 156, 11, 76, 57, 8, 33, 3, 35, 75, 15, 194, 66, 52, 117, 149, 56, 41, 157, 141, 73, 49, 39, 158, 169, 71, 175, 122, 197, 34, 25, 115, 173, 14, 134, 201, 205, 26, 192, 188, 119, 110, 137, 69, 180, 46, 21, 24, 103, 10, 132, 0]], Length: 211\n",
      "Vehicle 0: 66893 m, 466.116 min, including 15.223 mins waiting time.\n",
      "Total distance of all routes: : 66893 m\n",
      "Maximum travel time: 466.116 min\n",
      "VRP-R\n",
      "Routes: [[0, 193, 95, 191, 53, 198, 167, 136, 88, 91, 19, 40, 127, 50, 116, 139, 7, 171, 29, 178, 145, 181, 54, 47, 20, 177, 37, 51, 80, 154, 186, 162, 62, 118, 42, 120, 112, 202, 32, 163, 64, 199, 200, 114, 27, 67, 174, 98, 43, 1, 195, 151, 160, 94, 170, 179, 48, 155, 68, 17, 83, 143, 9, 150, 165, 65, 187, 4, 106, 105, 61, 92, 189, 45, 18, 96, 125, 168, 123, 133, 84, 72, 131, 111, 60, 79, 97, 184, 44, 148, 109, 108, 86, 55, 101, 93, 176, 5, 82, 121, 6, 23, 185, 85, 102, 104, 142, 182, 58, 209, 12, 124, 172, 99, 90, 166, 130, 206, 128, 74, 113, 77, 36, 204, 146, 190, 135, 164, 59, 38, 208, 2, 107, 153, 28, 126, 183, 147, 138, 207, 30, 89, 152, 161, 78, 196, 144, 31, 22, 13, 203, 140, 129, 63, 100, 87, 70, 16, 159, 81, 156, 11, 76, 57, 8, 33, 3, 35, 75, 15, 194, 66, 52, 117, 149, 56, 41, 157, 141, 73, 49, 39, 158, 169, 71, 175, 122, 197, 34, 25, 115, 173, 14, 134, 201, 205, 26, 192, 188, 119, 110, 137, 69, 180, 46, 21, 24, 103, 10, 132, 0]], Length: 211\n",
      "Robot Routes: [[[196, 144, 31, 22, 13, 203, 140, 129, 63, 100, 87, 70], [90, 166, 130, 206, 128, 74, 113, 77, 36, 204, 146, 190], [131, 111, 60, 79, 97, 184, 44, 148, 109, 108, 86, 55], [23, 185, 85, 102, 104, 142, 182, 58, 209, 12, 124, 172], [68, 17, 83, 143, 9, 150, 165, 65, 187, 4, 106, 105], [53, 198, 167, 136, 88, 91, 19, 40, 127, 50, 116, 139]]]\n",
      "Route: [0, 193, 95, 191, 53, 139, 7, 171, 29, 178, 145, 181, 54, 47, 20, 177, 37, 51, 80, 154, 186, 162, 62, 118, 42, 120, 112, 202, 32, 163, 64, 199, 200, 114, 27, 67, 174, 98, 43, 1, 195, 151, 160, 94, 170, 179, 48, 155, 68, 105, 61, 92, 189, 45, 18, 96, 125, 168, 123, 133, 84, 72, 131, 55, 101, 93, 176, 5, 82, 121, 6, 23, 172, 99, 90, 190, 135, 164, 59, 38, 208, 2, 107, 153, 28, 126, 183, 147, 138, 207, 30, 89, 152, 161, 78, 196, 70, 16, 159, 81, 156, 11, 76, 57, 8, 33, 3, 35, 75, 15, 194, 66, 52, 117, 149, 56, 41, 157, 141, 73, 49, 39, 158, 169, 71, 175, 122, 197, 34, 25, 115, 173, 14, 134, 201, 205, 26, 192, 188, 119, 110, 137, 69, 180, 46, 21, 24, 103, 10, 132, 0], Robot Group: [[196, 144, 31, 22, 13, 203, 140, 129, 63, 100, 87, 70], [90, 166, 130, 206, 128, 74, 113, 77, 36, 204, 146, 190], [131, 111, 60, 79, 97, 184, 44, 148, 109, 108, 86, 55], [23, 185, 85, 102, 104, 142, 182, 58, 209, 12, 124, 172], [68, 17, 83, 143, 9, 150, 165, 65, 187, 4, 106, 105], [53, 198, 167, 136, 88, 91, 19, 40, 127, 50, 116, 139]]\n",
      "Vehicle 0: 60293 m, 395.555 min, including 35.262 mins waiting time.\n",
      "Total distance of all routes: : 60293 m\n",
      "Maximum travel time: 395.555 min\n",
      "VRP-RD\n",
      "Routes: [[0, 193, 95, 191, 53, 198, 167, 136, 88, 91, 19, 40, 127, 50, 116, 139, 7, 171, 29, 178, 145, 181, 54, 47, 20, 177, 37, 51, 80, 154, 186, 162, 62, 118, 42, 120, 112, 202, 32, 163, 64, 199, 200, 114, 27, 67, 174, 98, 43, 1, 195, 151, 160, 94, 170, 179, 48, 155, 68, 17, 83, 143, 9, 150, 165, 65, 187, 4, 106, 105, 61, 92, 189, 45, 18, 96, 125, 168, 123, 133, 84, 72, 131, 111, 60, 79, 97, 184, 44, 148, 109, 108, 86, 55, 101, 93, 176, 5, 82, 121, 6, 23, 185, 85, 102, 104, 142, 182, 58, 209, 12, 124, 172, 99, 90, 166, 130, 206, 128, 74, 113, 77, 36, 204, 146, 190, 135, 164, 59, 38, 208, 2, 107, 153, 28, 126, 183, 147, 138, 207, 30, 89, 152, 161, 78, 196, 144, 31, 22, 13, 203, 140, 129, 63, 100, 87, 70, 16, 159, 81, 156, 11, 76, 57, 8, 33, 3, 35, 75, 15, 194, 66, 52, 117, 149, 56, 41, 157, 141, 73, 49, 39, 158, 169, 71, 175, 122, 197, 34, 25, 115, 173, 14, 134, 201, 205, 26, 192, 188, 119, 110, 137, 69, 180, 46, 21, 24, 103, 10, 132, 0]], Length: 211\n",
      "Robot Routes: [[[196, 144, 31, 22, 13, 203, 140, 129, 63, 100, 87, 70], [90, 166, 130, 206, 128, 74, 113, 77, 36, 204, 146, 190], [131, 111, 60, 79, 97, 184, 44, 148, 109, 108, 86, 55], [23, 185, 85, 102, 104, 142, 182, 58, 209, 12, 124, 172], [68, 17, 83, 143, 9, 150, 165, 65, 187, 4, 106, 105], [53, 198, 167, 136, 88, 91, 19, 40, 127, 50, 116, 139]]]\n",
      "Route: [0, 193, 95, 191, 53, 139, 7, 171, 29, 178, 145, 181, 54, 47, 20, 177, 37, 51, 80, 154, 186, 162, 62, 118, 42, 120, 112, 202, 32, 163, 64, 199, 200, 114, 27, 67, 174, 98, 43, 1, 195, 151, 160, 94, 170, 179, 48, 155, 68, 105, 61, 92, 189, 45, 18, 96, 125, 168, 123, 133, 84, 72, 131, 55, 101, 93, 176, 5, 82, 121, 6, 23, 172, 99, 90, 190, 135, 164, 59, 38, 208, 2, 107, 153, 28, 126, 183, 147, 138, 207, 30, 89, 152, 161, 78, 196, 70, 16, 159, 81, 156, 11, 76, 57, 8, 33, 3, 35, 75, 15, 194, 66, 52, 117, 149, 56, 41, 157, 141, 73, 49, 39, 158, 169, 71, 175, 122, 197, 34, 25, 115, 173, 14, 134, 201, 205, 26, 192, 188, 119, 110, 137, 69, 180, 46, 21, 24, 103, 10, 132, 0], Robot Group: [[196, 144, 31, 22, 13, 203, 140, 129, 63, 100, 87, 70], [90, 166, 130, 206, 128, 74, 113, 77, 36, 204, 146, 190], [131, 111, 60, 79, 97, 184, 44, 148, 109, 108, 86, 55], [23, 185, 85, 102, 104, 142, 182, 58, 209, 12, 124, 172], [68, 17, 83, 143, 9, 150, 165, 65, 187, 4, 106, 105], [53, 198, 167, 136, 88, 91, 19, 40, 127, 50, 116, 139]]\n",
      "Vehicle 0: 58739 m, 381.365 min, including 46.626 mins waiting time.\n",
      "Total distance of all routes: : 58739 m\n",
      "Maximum travel time: 381.365 min\n",
      "Trial 3...\n",
      "VRP\n",
      "Routes: [[0, 157, 170, 51, 29, 120, 136, 84, 203, 42, 137, 12, 48, 27, 147, 50, 145, 143, 54, 82, 161, 25, 20, 144, 193, 68, 3, 63, 21, 102, 99, 160, 92, 75, 195, 80, 47, 129, 108, 115, 110, 49, 15, 107, 6, 58, 79, 150, 104, 91, 176, 113, 131, 118, 65, 165, 85, 96, 97, 111, 70, 123, 175, 186, 81, 119, 44, 26, 43, 179, 36, 88, 192, 135, 149, 33, 116, 45, 4, 61, 132, 126, 17, 94, 74, 90, 184, 8, 208, 32, 128, 164, 206, 57, 194, 178, 124, 202, 53, 22, 1, 121, 188, 9, 180, 87, 197, 201, 199, 152, 30, 78, 52, 156, 77, 106, 177, 168, 66, 207, 171, 154, 172, 173, 7, 125, 189, 13, 205, 200, 86, 2, 162, 103, 127, 76, 46, 93, 190, 18, 64, 101, 169, 59, 31, 41, 89, 142, 130, 11, 138, 114, 105, 71, 28, 98, 100, 140, 122, 60, 191, 112, 16, 167, 139, 23, 158, 198, 95, 55, 204, 5, 34, 174, 83, 62, 166, 151, 109, 182, 19, 14, 72, 67, 133, 38, 163, 35, 159, 141, 73, 153, 196, 183, 209, 56, 39, 134, 40, 181, 24, 155, 185, 146, 10, 187, 37, 69, 117, 148, 0]], Length: 211\n",
      "Vehicle 0: 71037 m, 491.037 min, including 0 mins waiting time.\n",
      "Total distance of all routes: : 71037 m\n",
      "Maximum travel time: 491.037 min\n",
      "VRP-D\n",
      "Routes: [[0, 157, 170, 51, 29, 120, 136, 84, 203, 42, 137, 12, 48, 27, 147, 50, 145, 143, 54, 82, 161, 25, 20, 144, 193, 68, 3, 63, 21, 102, 99, 160, 92, 75, 195, 80, 47, 129, 108, 115, 110, 49, 15, 107, 6, 58, 79, 150, 104, 91, 176, 113, 131, 118, 65, 165, 85, 96, 97, 111, 70, 123, 175, 186, 81, 119, 44, 26, 43, 179, 36, 88, 192, 135, 149, 33, 116, 45, 4, 61, 132, 126, 17, 94, 74, 90, 184, 8, 208, 32, 128, 164, 206, 57, 194, 178, 124, 202, 53, 22, 1, 121, 188, 9, 180, 87, 197, 201, 199, 152, 30, 78, 52, 156, 77, 106, 177, 168, 66, 207, 171, 154, 172, 173, 7, 125, 189, 13, 205, 200, 86, 2, 162, 103, 127, 76, 46, 93, 190, 18, 64, 101, 169, 59, 31, 41, 89, 142, 130, 11, 138, 114, 105, 71, 28, 98, 100, 140, 122, 60, 191, 112, 16, 167, 139, 23, 158, 198, 95, 55, 204, 5, 34, 174, 83, 62, 166, 151, 109, 182, 19, 14, 72, 67, 133, 38, 163, 35, 159, 141, 73, 153, 196, 183, 209, 56, 39, 134, 40, 181, 24, 155, 185, 146, 10, 187, 37, 69, 117, 148, 0]], Length: 211\n",
      "Vehicle 0: 66541 m, 465.025 min, including 16.484 mins waiting time.\n",
      "Total distance of all routes: : 66541 m\n",
      "Maximum travel time: 465.025 min\n",
      "VRP-R\n",
      "Routes: [[0, 157, 170, 51, 29, 120, 136, 84, 203, 42, 137, 12, 48, 27, 147, 50, 145, 143, 54, 82, 161, 25, 20, 144, 193, 68, 3, 63, 21, 102, 99, 160, 92, 75, 195, 80, 47, 129, 108, 115, 110, 49, 15, 107, 6, 58, 79, 150, 104, 91, 176, 113, 131, 118, 65, 165, 85, 96, 97, 111, 70, 123, 175, 186, 81, 119, 44, 26, 43, 179, 36, 88, 192, 135, 149, 33, 116, 45, 4, 61, 132, 126, 17, 94, 74, 90, 184, 8, 208, 32, 128, 164, 206, 57, 194, 178, 124, 202, 53, 22, 1, 121, 188, 9, 180, 87, 197, 201, 199, 152, 30, 78, 52, 156, 77, 106, 177, 168, 66, 207, 171, 154, 172, 173, 7, 125, 189, 13, 205, 200, 86, 2, 162, 103, 127, 76, 46, 93, 190, 18, 64, 101, 169, 59, 31, 41, 89, 142, 130, 11, 138, 114, 105, 71, 28, 98, 100, 140, 122, 60, 191, 112, 16, 167, 139, 23, 158, 198, 95, 55, 204, 5, 34, 174, 83, 62, 166, 151, 109, 182, 19, 14, 72, 67, 133, 38, 163, 35, 159, 141, 73, 153, 196, 183, 209, 56, 39, 134, 40, 181, 24, 155, 185, 146, 10, 187, 37, 69, 117, 148, 0]], Length: 211\n",
      "Robot Routes: [[[184, 8, 208, 32, 128, 164, 206, 57, 194, 178, 124, 202], [59, 31, 41, 89, 142, 130, 11, 138, 114, 105, 71, 28], [177, 168, 66, 207, 171, 154, 172, 173, 7, 125, 189, 13], [67, 133, 38, 163, 35, 159, 141, 73, 153, 196, 183, 209], [1, 121, 188, 9, 180, 87, 197, 201, 199, 152, 30, 78], [191, 112, 16, 167, 139, 23, 158, 198, 95, 55, 204, 5], [6, 58, 79, 150, 104, 91, 176, 113, 131, 118, 65, 165]]]\n",
      "Route: [0, 157, 170, 51, 29, 120, 136, 84, 203, 42, 137, 12, 48, 27, 147, 50, 145, 143, 54, 82, 161, 25, 20, 144, 193, 68, 3, 63, 21, 102, 99, 160, 92, 75, 195, 80, 47, 129, 108, 115, 110, 49, 15, 107, 6, 165, 85, 96, 97, 111, 70, 123, 175, 186, 81, 119, 44, 26, 43, 179, 36, 88, 192, 135, 149, 33, 116, 45, 4, 61, 132, 126, 17, 94, 74, 90, 184, 202, 53, 22, 1, 78, 52, 156, 77, 106, 177, 13, 205, 200, 86, 2, 162, 103, 127, 76, 46, 93, 190, 18, 64, 101, 169, 59, 28, 98, 100, 140, 122, 60, 191, 5, 34, 174, 83, 62, 166, 151, 109, 182, 19, 14, 72, 67, 209, 56, 39, 134, 40, 181, 24, 155, 185, 146, 10, 187, 37, 69, 117, 148, 0], Robot Group: [[184, 8, 208, 32, 128, 164, 206, 57, 194, 178, 124, 202], [59, 31, 41, 89, 142, 130, 11, 138, 114, 105, 71, 28], [177, 168, 66, 207, 171, 154, 172, 173, 7, 125, 189, 13], [67, 133, 38, 163, 35, 159, 141, 73, 153, 196, 183, 209], [1, 121, 188, 9, 180, 87, 197, 201, 199, 152, 30, 78], [191, 112, 16, 167, 139, 23, 158, 198, 95, 55, 204, 5], [6, 58, 79, 150, 104, 91, 176, 113, 131, 118, 65, 165]]\n",
      "Vehicle 0: 62444 m, 371.766 min, including 29.322 mins waiting time.\n",
      "Total distance of all routes: : 62444 m\n",
      "Maximum travel time: 371.766 min\n",
      "VRP-RD\n",
      "Routes: [[0, 157, 170, 51, 29, 120, 136, 84, 203, 42, 137, 12, 48, 27, 147, 50, 145, 143, 54, 82, 161, 25, 20, 144, 193, 68, 3, 63, 21, 102, 99, 160, 92, 75, 195, 80, 47, 129, 108, 115, 110, 49, 15, 107, 6, 58, 79, 150, 104, 91, 176, 113, 131, 118, 65, 165, 85, 96, 97, 111, 70, 123, 175, 186, 81, 119, 44, 26, 43, 179, 36, 88, 192, 135, 149, 33, 116, 45, 4, 61, 132, 126, 17, 94, 74, 90, 184, 8, 208, 32, 128, 164, 206, 57, 194, 178, 124, 202, 53, 22, 1, 121, 188, 9, 180, 87, 197, 201, 199, 152, 30, 78, 52, 156, 77, 106, 177, 168, 66, 207, 171, 154, 172, 173, 7, 125, 189, 13, 205, 200, 86, 2, 162, 103, 127, 76, 46, 93, 190, 18, 64, 101, 169, 59, 31, 41, 89, 142, 130, 11, 138, 114, 105, 71, 28, 98, 100, 140, 122, 60, 191, 112, 16, 167, 139, 23, 158, 198, 95, 55, 204, 5, 34, 174, 83, 62, 166, 151, 109, 182, 19, 14, 72, 67, 133, 38, 163, 35, 159, 141, 73, 153, 196, 183, 209, 56, 39, 134, 40, 181, 24, 155, 185, 146, 10, 187, 37, 69, 117, 148, 0]], Length: 211\n",
      "Robot Routes: [[[184, 8, 208, 32, 128, 164, 206, 57, 194, 178, 124, 202], [59, 31, 41, 89, 142, 130, 11, 138, 114, 105, 71, 28], [177, 168, 66, 207, 171, 154, 172, 173, 7, 125, 189, 13], [67, 133, 38, 163, 35, 159, 141, 73, 153, 196, 183, 209], [1, 121, 188, 9, 180, 87, 197, 201, 199, 152, 30, 78], [191, 112, 16, 167, 139, 23, 158, 198, 95, 55, 204, 5], [6, 58, 79, 150, 104, 91, 176, 113, 131, 118, 65, 165]]]\n",
      "Route: [0, 157, 170, 51, 29, 120, 136, 84, 203, 42, 137, 12, 48, 27, 147, 50, 145, 143, 54, 82, 161, 25, 20, 144, 193, 68, 3, 63, 21, 102, 99, 160, 92, 75, 195, 80, 47, 129, 108, 115, 110, 49, 15, 107, 6, 165, 85, 96, 97, 111, 70, 123, 175, 186, 81, 119, 44, 26, 43, 179, 36, 88, 192, 135, 149, 33, 116, 45, 4, 61, 132, 126, 17, 94, 74, 90, 184, 202, 53, 22, 1, 78, 52, 156, 77, 106, 177, 13, 205, 200, 86, 2, 162, 103, 127, 76, 46, 93, 190, 18, 64, 101, 169, 59, 28, 98, 100, 140, 122, 60, 191, 5, 34, 174, 83, 62, 166, 151, 109, 182, 19, 14, 72, 67, 209, 56, 39, 134, 40, 181, 24, 155, 185, 146, 10, 187, 37, 69, 117, 148, 0], Robot Group: [[184, 8, 208, 32, 128, 164, 206, 57, 194, 178, 124, 202], [59, 31, 41, 89, 142, 130, 11, 138, 114, 105, 71, 28], [177, 168, 66, 207, 171, 154, 172, 173, 7, 125, 189, 13], [67, 133, 38, 163, 35, 159, 141, 73, 153, 196, 183, 209], [1, 121, 188, 9, 180, 87, 197, 201, 199, 152, 30, 78], [191, 112, 16, 167, 139, 23, 158, 198, 95, 55, 204, 5], [6, 58, 79, 150, 104, 91, 176, 113, 131, 118, 65, 165]]\n",
      "Vehicle 0: 60165 m, 360.441 min, including 40.276 mins waiting time.\n",
      "Total distance of all routes: : 60165 m\n",
      "Maximum travel time: 360.441 min\n",
      "Trial 4...\n",
      "VRP\n",
      "Routes: [[0, 89, 154, 150, 55, 182, 173, 137, 166, 181, 141, 186, 171, 22, 31, 149, 79, 51, 58, 163, 104, 95, 165, 83, 209, 103, 128, 2, 183, 68, 60, 39, 168, 196, 178, 23, 113, 30, 65, 101, 19, 200, 135, 96, 18, 21, 142, 131, 35, 117, 27, 28, 15, 124, 85, 111, 136, 74, 92, 82, 81, 87, 172, 36, 140, 6, 107, 100, 160, 43, 69, 64, 66, 12, 84, 153, 198, 129, 126, 125, 91, 120, 56, 67, 76, 174, 99, 53, 98, 191, 123, 118, 41, 194, 1, 145, 45, 156, 169, 63, 151, 7, 4, 170, 110, 143, 138, 139, 5, 52, 152, 176, 62, 206, 32, 134, 77, 46, 86, 90, 16, 10, 175, 93, 162, 80, 72, 109, 195, 204, 190, 127, 164, 203, 49, 132, 61, 73, 144, 197, 146, 193, 24, 147, 3, 102, 159, 20, 133, 37, 192, 112, 167, 59, 184, 121, 189, 208, 180, 155, 179, 71, 185, 50, 158, 130, 148, 187, 105, 115, 38, 78, 34, 11, 199, 13, 94, 119, 205, 177, 57, 29, 26, 108, 202, 17, 88, 42, 47, 106, 9, 33, 44, 40, 14, 122, 54, 8, 157, 97, 70, 201, 116, 48, 188, 114, 161, 207, 25, 75, 0]], Length: 211\n",
      "Vehicle 0: 72610 m, 492.61 min, including 0 mins waiting time.\n",
      "Total distance of all routes: : 72610 m\n",
      "Maximum travel time: 492.61 min\n",
      "VRP-D\n",
      "Routes: [[0, 89, 154, 150, 55, 182, 173, 137, 166, 181, 141, 186, 171, 22, 31, 149, 79, 51, 58, 163, 104, 95, 165, 83, 209, 103, 128, 2, 183, 68, 60, 39, 168, 196, 178, 23, 113, 30, 65, 101, 19, 200, 135, 96, 18, 21, 142, 131, 35, 117, 27, 28, 15, 124, 85, 111, 136, 74, 92, 82, 81, 87, 172, 36, 140, 6, 107, 100, 160, 43, 69, 64, 66, 12, 84, 153, 198, 129, 126, 125, 91, 120, 56, 67, 76, 174, 99, 53, 98, 191, 123, 118, 41, 194, 1, 145, 45, 156, 169, 63, 151, 7, 4, 170, 110, 143, 138, 139, 5, 52, 152, 176, 62, 206, 32, 134, 77, 46, 86, 90, 16, 10, 175, 93, 162, 80, 72, 109, 195, 204, 190, 127, 164, 203, 49, 132, 61, 73, 144, 197, 146, 193, 24, 147, 3, 102, 159, 20, 133, 37, 192, 112, 167, 59, 184, 121, 189, 208, 180, 155, 179, 71, 185, 50, 158, 130, 148, 187, 105, 115, 38, 78, 34, 11, 199, 13, 94, 119, 205, 177, 57, 29, 26, 108, 202, 17, 88, 42, 47, 106, 9, 33, 44, 40, 14, 122, 54, 8, 157, 97, 70, 201, 116, 48, 188, 114, 161, 207, 25, 75, 0]], Length: 211\n",
      "Vehicle 0: 69393 m, 469.476 min, including 14.083 mins waiting time.\n",
      "Total distance of all routes: : 69393 m\n",
      "Maximum travel time: 469.476 min\n",
      "VRP-R\n",
      "Routes: [[0, 89, 154, 150, 55, 182, 173, 137, 166, 181, 141, 186, 171, 22, 31, 149, 79, 51, 58, 163, 104, 95, 165, 83, 209, 103, 128, 2, 183, 68, 60, 39, 168, 196, 178, 23, 113, 30, 65, 101, 19, 200, 135, 96, 18, 21, 142, 131, 35, 117, 27, 28, 15, 124, 85, 111, 136, 74, 92, 82, 81, 87, 172, 36, 140, 6, 107, 100, 160, 43, 69, 64, 66, 12, 84, 153, 198, 129, 126, 125, 91, 120, 56, 67, 76, 174, 99, 53, 98, 191, 123, 118, 41, 194, 1, 145, 45, 156, 169, 63, 151, 7, 4, 170, 110, 143, 138, 139, 5, 52, 152, 176, 62, 206, 32, 134, 77, 46, 86, 90, 16, 10, 175, 93, 162, 80, 72, 109, 195, 204, 190, 127, 164, 203, 49, 132, 61, 73, 144, 197, 146, 193, 24, 147, 3, 102, 159, 20, 133, 37, 192, 112, 167, 59, 184, 121, 189, 208, 180, 155, 179, 71, 185, 50, 158, 130, 148, 187, 105, 115, 38, 78, 34, 11, 199, 13, 94, 119, 205, 177, 57, 29, 26, 108, 202, 17, 88, 42, 47, 106, 9, 33, 44, 40, 14, 122, 54, 8, 157, 97, 70, 201, 116, 48, 188, 114, 161, 207, 25, 75, 0]], Length: 211\n",
      "Robot Routes: [[[92, 82, 81, 87, 172, 36, 140, 6, 107, 100, 160, 43], [26, 108, 202, 17, 88, 42, 47, 106, 9, 33, 44, 40], [193, 24, 147, 3, 102, 159, 20, 133, 37, 192, 112, 167], [7, 4, 170, 110, 143, 138, 139, 5, 52, 152, 176, 62], [39, 168, 196, 178, 23, 113, 30, 65, 101, 19, 200, 135], [191, 123, 118, 41, 194, 1, 145, 45, 156, 169, 63, 151], [18, 21, 142, 131, 35, 117, 27, 28, 15, 124, 85, 111], [186, 171, 22, 31, 149, 79, 51, 58, 163, 104, 95, 165]]]\n",
      "Route: [0, 89, 154, 150, 55, 182, 173, 137, 166, 181, 141, 186, 165, 83, 209, 103, 128, 2, 183, 68, 60, 39, 135, 96, 18, 111, 136, 74, 92, 43, 69, 64, 66, 12, 84, 153, 198, 129, 126, 125, 91, 120, 56, 67, 76, 174, 99, 53, 98, 191, 151, 7, 62, 206, 32, 134, 77, 46, 86, 90, 16, 10, 175, 93, 162, 80, 72, 109, 195, 204, 190, 127, 164, 203, 49, 132, 61, 73, 144, 197, 146, 193, 167, 59, 184, 121, 189, 208, 180, 155, 179, 71, 185, 50, 158, 130, 148, 187, 105, 115, 38, 78, 34, 11, 199, 13, 94, 119, 205, 177, 57, 29, 26, 40, 14, 122, 54, 8, 157, 97, 70, 201, 116, 48, 188, 114, 161, 207, 25, 75, 0], Robot Group: [[92, 82, 81, 87, 172, 36, 140, 6, 107, 100, 160, 43], [26, 108, 202, 17, 88, 42, 47, 106, 9, 33, 44, 40], [193, 24, 147, 3, 102, 159, 20, 133, 37, 192, 112, 167], [7, 4, 170, 110, 143, 138, 139, 5, 52, 152, 176, 62], [39, 168, 196, 178, 23, 113, 30, 65, 101, 19, 200, 135], [191, 123, 118, 41, 194, 1, 145, 45, 156, 169, 63, 151], [18, 21, 142, 131, 35, 117, 27, 28, 15, 124, 85, 111], [186, 171, 22, 31, 149, 79, 51, 58, 163, 104, 95, 165]]\n",
      "Vehicle 0: 58829 m, 357.983 min, including 39.154 mins waiting time.\n",
      "Total distance of all routes: : 58829 m\n",
      "Maximum travel time: 357.983 min\n",
      "VRP-RD\n",
      "Routes: [[0, 89, 154, 150, 55, 182, 173, 137, 166, 181, 141, 186, 171, 22, 31, 149, 79, 51, 58, 163, 104, 95, 165, 83, 209, 103, 128, 2, 183, 68, 60, 39, 168, 196, 178, 23, 113, 30, 65, 101, 19, 200, 135, 96, 18, 21, 142, 131, 35, 117, 27, 28, 15, 124, 85, 111, 136, 74, 92, 82, 81, 87, 172, 36, 140, 6, 107, 100, 160, 43, 69, 64, 66, 12, 84, 153, 198, 129, 126, 125, 91, 120, 56, 67, 76, 174, 99, 53, 98, 191, 123, 118, 41, 194, 1, 145, 45, 156, 169, 63, 151, 7, 4, 170, 110, 143, 138, 139, 5, 52, 152, 176, 62, 206, 32, 134, 77, 46, 86, 90, 16, 10, 175, 93, 162, 80, 72, 109, 195, 204, 190, 127, 164, 203, 49, 132, 61, 73, 144, 197, 146, 193, 24, 147, 3, 102, 159, 20, 133, 37, 192, 112, 167, 59, 184, 121, 189, 208, 180, 155, 179, 71, 185, 50, 158, 130, 148, 187, 105, 115, 38, 78, 34, 11, 199, 13, 94, 119, 205, 177, 57, 29, 26, 108, 202, 17, 88, 42, 47, 106, 9, 33, 44, 40, 14, 122, 54, 8, 157, 97, 70, 201, 116, 48, 188, 114, 161, 207, 25, 75, 0]], Length: 211\n",
      "Robot Routes: [[[92, 82, 81, 87, 172, 36, 140, 6, 107, 100, 160, 43], [26, 108, 202, 17, 88, 42, 47, 106, 9, 33, 44, 40], [193, 24, 147, 3, 102, 159, 20, 133, 37, 192, 112, 167], [7, 4, 170, 110, 143, 138, 139, 5, 52, 152, 176, 62], [39, 168, 196, 178, 23, 113, 30, 65, 101, 19, 200, 135], [191, 123, 118, 41, 194, 1, 145, 45, 156, 169, 63, 151], [18, 21, 142, 131, 35, 117, 27, 28, 15, 124, 85, 111], [186, 171, 22, 31, 149, 79, 51, 58, 163, 104, 95, 165]]]\n",
      "Route: [0, 89, 154, 150, 55, 182, 173, 137, 166, 181, 141, 186, 165, 83, 209, 103, 128, 2, 183, 68, 60, 39, 135, 96, 18, 111, 136, 74, 92, 43, 69, 64, 66, 12, 84, 153, 198, 129, 126, 125, 91, 120, 56, 67, 76, 174, 99, 53, 98, 191, 151, 7, 62, 206, 32, 134, 77, 46, 86, 90, 16, 10, 175, 93, 162, 80, 72, 109, 195, 204, 190, 127, 164, 203, 49, 132, 61, 73, 144, 197, 146, 193, 167, 59, 184, 121, 189, 208, 180, 155, 179, 71, 185, 50, 158, 130, 148, 187, 105, 115, 38, 78, 34, 11, 199, 13, 94, 119, 205, 177, 57, 29, 26, 40, 14, 122, 54, 8, 157, 97, 70, 201, 116, 48, 188, 114, 161, 207, 25, 75, 0], Robot Group: [[92, 82, 81, 87, 172, 36, 140, 6, 107, 100, 160, 43], [26, 108, 202, 17, 88, 42, 47, 106, 9, 33, 44, 40], [193, 24, 147, 3, 102, 159, 20, 133, 37, 192, 112, 167], [7, 4, 170, 110, 143, 138, 139, 5, 52, 152, 176, 62], [39, 168, 196, 178, 23, 113, 30, 65, 101, 19, 200, 135], [191, 123, 118, 41, 194, 1, 145, 45, 156, 169, 63, 151], [18, 21, 142, 131, 35, 117, 27, 28, 15, 124, 85, 111], [186, 171, 22, 31, 149, 79, 51, 58, 163, 104, 95, 165]]\n",
      "Vehicle 0: 55770 m, 350.739 min, including 52.969 mins waiting time.\n",
      "Total distance of all routes: : 55770 m\n",
      "Maximum travel time: 350.739 min\n",
      "Trial 5...\n",
      "VRP\n",
      "Routes: [[0, 4, 22, 116, 70, 85, 36, 193, 142, 110, 198, 62, 184, 207, 49, 106, 72, 90, 52, 109, 5, 133, 29, 54, 100, 153, 117, 103, 129, 189, 45, 182, 60, 75, 18, 140, 203, 130, 107, 160, 159, 176, 199, 194, 13, 205, 47, 65, 40, 19, 8, 126, 112, 195, 39, 101, 12, 208, 191, 92, 53, 21, 135, 204, 157, 114, 74, 10, 169, 16, 146, 55, 179, 97, 178, 170, 138, 82, 181, 168, 28, 14, 115, 30, 24, 11, 1, 152, 128, 108, 48, 165, 25, 145, 139, 32, 122, 81, 69, 196, 183, 2, 37, 91, 59, 57, 50, 78, 73, 71, 125, 67, 95, 104, 42, 127, 87, 190, 80, 56, 148, 131, 111, 113, 171, 137, 154, 173, 202, 174, 164, 105, 93, 177, 79, 149, 63, 119, 64, 15, 3, 134, 163, 96, 175, 158, 192, 68, 124, 123, 102, 147, 156, 23, 51, 6, 136, 58, 66, 188, 206, 41, 200, 144, 46, 9, 141, 185, 166, 20, 201, 84, 99, 120, 86, 197, 35, 187, 7, 61, 33, 31, 167, 98, 180, 161, 132, 26, 88, 151, 172, 155, 150, 77, 209, 162, 38, 83, 121, 34, 43, 94, 118, 186, 27, 89, 44, 143, 76, 17, 0]], Length: 211\n",
      "Vehicle 0: 69674 m, 489.674 min, including 0 mins waiting time.\n",
      "Total distance of all routes: : 69674 m\n",
      "Maximum travel time: 489.674 min\n",
      "VRP-D\n",
      "Routes: [[0, 4, 22, 116, 70, 85, 36, 193, 142, 110, 198, 62, 184, 207, 49, 106, 72, 90, 52, 109, 5, 133, 29, 54, 100, 153, 117, 103, 129, 189, 45, 182, 60, 75, 18, 140, 203, 130, 107, 160, 159, 176, 199, 194, 13, 205, 47, 65, 40, 19, 8, 126, 112, 195, 39, 101, 12, 208, 191, 92, 53, 21, 135, 204, 157, 114, 74, 10, 169, 16, 146, 55, 179, 97, 178, 170, 138, 82, 181, 168, 28, 14, 115, 30, 24, 11, 1, 152, 128, 108, 48, 165, 25, 145, 139, 32, 122, 81, 69, 196, 183, 2, 37, 91, 59, 57, 50, 78, 73, 71, 125, 67, 95, 104, 42, 127, 87, 190, 80, 56, 148, 131, 111, 113, 171, 137, 154, 173, 202, 174, 164, 105, 93, 177, 79, 149, 63, 119, 64, 15, 3, 134, 163, 96, 175, 158, 192, 68, 124, 123, 102, 147, 156, 23, 51, 6, 136, 58, 66, 188, 206, 41, 200, 144, 46, 9, 141, 185, 166, 20, 201, 84, 99, 120, 86, 197, 35, 187, 7, 61, 33, 31, 167, 98, 180, 161, 132, 26, 88, 151, 172, 155, 150, 77, 209, 162, 38, 83, 121, 34, 43, 94, 118, 186, 27, 89, 44, 143, 76, 17, 0]], Length: 211\n",
      "Vehicle 0: 67298 m, 466.213 min, including 12.915 mins waiting time.\n",
      "Total distance of all routes: : 67298 m\n",
      "Maximum travel time: 466.213 min\n",
      "VRP-R\n",
      "Routes: [[0, 4, 22, 116, 70, 85, 36, 193, 142, 110, 198, 62, 184, 207, 49, 106, 72, 90, 52, 109, 5, 133, 29, 54, 100, 153, 117, 103, 129, 189, 45, 182, 60, 75, 18, 140, 203, 130, 107, 160, 159, 176, 199, 194, 13, 205, 47, 65, 40, 19, 8, 126, 112, 195, 39, 101, 12, 208, 191, 92, 53, 21, 135, 204, 157, 114, 74, 10, 169, 16, 146, 55, 179, 97, 178, 170, 138, 82, 181, 168, 28, 14, 115, 30, 24, 11, 1, 152, 128, 108, 48, 165, 25, 145, 139, 32, 122, 81, 69, 196, 183, 2, 37, 91, 59, 57, 50, 78, 73, 71, 125, 67, 95, 104, 42, 127, 87, 190, 80, 56, 148, 131, 111, 113, 171, 137, 154, 173, 202, 174, 164, 105, 93, 177, 79, 149, 63, 119, 64, 15, 3, 134, 163, 96, 175, 158, 192, 68, 124, 123, 102, 147, 156, 23, 51, 6, 136, 58, 66, 188, 206, 41, 200, 144, 46, 9, 141, 185, 166, 20, 201, 84, 99, 120, 86, 197, 35, 187, 7, 61, 33, 31, 167, 98, 180, 161, 132, 26, 88, 151, 172, 155, 150, 77, 209, 162, 38, 83, 121, 34, 43, 94, 118, 186, 27, 89, 44, 143, 76, 17, 0]], Length: 211\n",
      "Robot Routes: [[[52, 109, 5, 133, 29, 54, 100, 153, 117, 103, 129, 189], [65, 40, 19, 8, 126, 112, 195, 39, 101, 12, 208, 191], [23, 51, 6, 136, 58, 66, 188, 206, 41, 200, 144, 46], [87, 190, 80, 56, 148, 131, 111, 113, 171, 137, 154, 173], [34, 43, 94, 118, 186, 27, 89, 44, 143, 76, 17, 0], [105, 93, 177, 79, 149, 63, 119, 64, 15, 3, 134, 163]]]\n",
      "Route: [0, 4, 22, 116, 70, 85, 36, 193, 142, 110, 198, 62, 184, 207, 49, 106, 72, 90, 52, 189, 45, 182, 60, 75, 18, 140, 203, 130, 107, 160, 159, 176, 199, 194, 13, 205, 47, 65, 191, 92, 53, 21, 135, 204, 157, 114, 74, 10, 169, 16, 146, 55, 179, 97, 178, 170, 138, 82, 181, 168, 28, 14, 115, 30, 24, 11, 1, 152, 128, 108, 48, 165, 25, 145, 139, 32, 122, 81, 69, 196, 183, 2, 37, 91, 59, 57, 50, 78, 73, 71, 125, 67, 95, 104, 42, 127, 87, 173, 202, 174, 164, 105, 163, 96, 175, 158, 192, 68, 124, 123, 102, 147, 156, 23, 46, 9, 141, 185, 166, 20, 201, 84, 99, 120, 86, 197, 35, 187, 7, 61, 33, 31, 167, 98, 180, 161, 132, 26, 88, 151, 172, 155, 150, 77, 209, 162, 38, 83, 121, 34, 0], Robot Group: [[52, 109, 5, 133, 29, 54, 100, 153, 117, 103, 129, 189], [65, 40, 19, 8, 126, 112, 195, 39, 101, 12, 208, 191], [23, 51, 6, 136, 58, 66, 188, 206, 41, 200, 144, 46], [87, 190, 80, 56, 148, 131, 111, 113, 171, 137, 154, 173], [34, 43, 94, 118, 186, 27, 89, 44, 143, 76, 17, 0], [105, 93, 177, 79, 149, 63, 119, 64, 15, 3, 134, 163]]\n",
      "Vehicle 0: 61682 m, 396.735 min, including 33.053 mins waiting time.\n",
      "Total distance of all routes: : 61682 m\n",
      "Maximum travel time: 396.735 min\n",
      "VRP-RD\n",
      "Routes: [[0, 4, 22, 116, 70, 85, 36, 193, 142, 110, 198, 62, 184, 207, 49, 106, 72, 90, 52, 109, 5, 133, 29, 54, 100, 153, 117, 103, 129, 189, 45, 182, 60, 75, 18, 140, 203, 130, 107, 160, 159, 176, 199, 194, 13, 205, 47, 65, 40, 19, 8, 126, 112, 195, 39, 101, 12, 208, 191, 92, 53, 21, 135, 204, 157, 114, 74, 10, 169, 16, 146, 55, 179, 97, 178, 170, 138, 82, 181, 168, 28, 14, 115, 30, 24, 11, 1, 152, 128, 108, 48, 165, 25, 145, 139, 32, 122, 81, 69, 196, 183, 2, 37, 91, 59, 57, 50, 78, 73, 71, 125, 67, 95, 104, 42, 127, 87, 190, 80, 56, 148, 131, 111, 113, 171, 137, 154, 173, 202, 174, 164, 105, 93, 177, 79, 149, 63, 119, 64, 15, 3, 134, 163, 96, 175, 158, 192, 68, 124, 123, 102, 147, 156, 23, 51, 6, 136, 58, 66, 188, 206, 41, 200, 144, 46, 9, 141, 185, 166, 20, 201, 84, 99, 120, 86, 197, 35, 187, 7, 61, 33, 31, 167, 98, 180, 161, 132, 26, 88, 151, 172, 155, 150, 77, 209, 162, 38, 83, 121, 34, 43, 94, 118, 186, 27, 89, 44, 143, 76, 17, 0]], Length: 211\n",
      "Robot Routes: [[[52, 109, 5, 133, 29, 54, 100, 153, 117, 103, 129, 189], [65, 40, 19, 8, 126, 112, 195, 39, 101, 12, 208, 191], [23, 51, 6, 136, 58, 66, 188, 206, 41, 200, 144, 46], [87, 190, 80, 56, 148, 131, 111, 113, 171, 137, 154, 173], [34, 43, 94, 118, 186, 27, 89, 44, 143, 76, 17, 0], [105, 93, 177, 79, 149, 63, 119, 64, 15, 3, 134, 163]]]\n",
      "Route: [0, 4, 22, 116, 70, 85, 36, 193, 142, 110, 198, 62, 184, 207, 49, 106, 72, 90, 52, 189, 45, 182, 60, 75, 18, 140, 203, 130, 107, 160, 159, 176, 199, 194, 13, 205, 47, 65, 191, 92, 53, 21, 135, 204, 157, 114, 74, 10, 169, 16, 146, 55, 179, 97, 178, 170, 138, 82, 181, 168, 28, 14, 115, 30, 24, 11, 1, 152, 128, 108, 48, 165, 25, 145, 139, 32, 122, 81, 69, 196, 183, 2, 37, 91, 59, 57, 50, 78, 73, 71, 125, 67, 95, 104, 42, 127, 87, 173, 202, 174, 164, 105, 163, 96, 175, 158, 192, 68, 124, 123, 102, 147, 156, 23, 46, 9, 141, 185, 166, 20, 201, 84, 99, 120, 86, 197, 35, 187, 7, 61, 33, 31, 167, 98, 180, 161, 132, 26, 88, 151, 172, 155, 150, 77, 209, 162, 38, 83, 121, 34, 0], Robot Group: [[52, 109, 5, 133, 29, 54, 100, 153, 117, 103, 129, 189], [65, 40, 19, 8, 126, 112, 195, 39, 101, 12, 208, 191], [23, 51, 6, 136, 58, 66, 188, 206, 41, 200, 144, 46], [87, 190, 80, 56, 148, 131, 111, 113, 171, 137, 154, 173], [34, 43, 94, 118, 186, 27, 89, 44, 143, 76, 17, 0], [105, 93, 177, 79, 149, 63, 119, 64, 15, 3, 134, 163]]\n",
      "Vehicle 0: 59509 m, 382.756 min, including 45.247 mins waiting time.\n",
      "Total distance of all routes: : 59509 m\n",
      "Maximum travel time: 382.756 min\n",
      "Trial 6...\n",
      "VRP\n",
      "Routes: [[0, 9, 180, 202, 149, 137, 98, 123, 18, 115, 43, 6, 73, 130, 36, 21, 67, 206, 90, 157, 11, 61, 30, 3, 177, 16, 172, 62, 127, 126, 34, 15, 182, 117, 108, 48, 129, 176, 192, 133, 147, 141, 128, 163, 93, 38, 86, 99, 23, 162, 33, 7, 77, 42, 142, 156, 195, 106, 181, 197, 199, 161, 205, 19, 179, 198, 124, 92, 59, 110, 103, 45, 17, 52, 56, 101, 37, 207, 63, 169, 66, 187, 74, 96, 114, 85, 113, 185, 164, 112, 87, 80, 138, 41, 152, 28, 58, 2, 10, 91, 160, 151, 204, 26, 97, 170, 203, 68, 193, 89, 100, 175, 49, 111, 71, 150, 29, 116, 20, 136, 186, 174, 191, 8, 40, 146, 135, 94, 143, 145, 79, 1, 122, 39, 196, 194, 70, 46, 50, 158, 53, 165, 167, 148, 189, 119, 140, 4, 12, 14, 173, 44, 64, 166, 184, 153, 171, 32, 188, 144, 190, 35, 154, 121, 25, 54, 134, 102, 55, 168, 139, 155, 132, 183, 201, 178, 159, 27, 57, 72, 109, 107, 65, 104, 209, 51, 47, 200, 60, 75, 22, 120, 69, 31, 83, 76, 118, 24, 131, 5, 84, 81, 105, 125, 208, 88, 95, 13, 82, 78, 0]], Length: 211\n",
      "Vehicle 0: 72625 m, 492.625 min, including 0 mins waiting time.\n",
      "Total distance of all routes: : 72625 m\n",
      "Maximum travel time: 492.625 min\n",
      "VRP-D\n",
      "Routes: [[0, 9, 180, 202, 149, 137, 98, 123, 18, 115, 43, 6, 73, 130, 36, 21, 67, 206, 90, 157, 11, 61, 30, 3, 177, 16, 172, 62, 127, 126, 34, 15, 182, 117, 108, 48, 129, 176, 192, 133, 147, 141, 128, 163, 93, 38, 86, 99, 23, 162, 33, 7, 77, 42, 142, 156, 195, 106, 181, 197, 199, 161, 205, 19, 179, 198, 124, 92, 59, 110, 103, 45, 17, 52, 56, 101, 37, 207, 63, 169, 66, 187, 74, 96, 114, 85, 113, 185, 164, 112, 87, 80, 138, 41, 152, 28, 58, 2, 10, 91, 160, 151, 204, 26, 97, 170, 203, 68, 193, 89, 100, 175, 49, 111, 71, 150, 29, 116, 20, 136, 186, 174, 191, 8, 40, 146, 135, 94, 143, 145, 79, 1, 122, 39, 196, 194, 70, 46, 50, 158, 53, 165, 167, 148, 189, 119, 140, 4, 12, 14, 173, 44, 64, 166, 184, 153, 171, 32, 188, 144, 190, 35, 154, 121, 25, 54, 134, 102, 55, 168, 139, 155, 132, 183, 201, 178, 159, 27, 57, 72, 109, 107, 65, 104, 209, 51, 47, 200, 60, 75, 22, 120, 69, 31, 83, 76, 118, 24, 131, 5, 84, 81, 105, 125, 208, 88, 95, 13, 82, 78, 0]], Length: 211\n",
      "Vehicle 0: 68578 m, 471.635 min, including 13.057 mins waiting time.\n",
      "Total distance of all routes: : 68578 m\n",
      "Maximum travel time: 471.635 min\n",
      "VRP-R\n",
      "Routes: [[0, 9, 180, 202, 149, 137, 98, 123, 18, 115, 43, 6, 73, 130, 36, 21, 67, 206, 90, 157, 11, 61, 30, 3, 177, 16, 172, 62, 127, 126, 34, 15, 182, 117, 108, 48, 129, 176, 192, 133, 147, 141, 128, 163, 93, 38, 86, 99, 23, 162, 33, 7, 77, 42, 142, 156, 195, 106, 181, 197, 199, 161, 205, 19, 179, 198, 124, 92, 59, 110, 103, 45, 17, 52, 56, 101, 37, 207, 63, 169, 66, 187, 74, 96, 114, 85, 113, 185, 164, 112, 87, 80, 138, 41, 152, 28, 58, 2, 10, 91, 160, 151, 204, 26, 97, 170, 203, 68, 193, 89, 100, 175, 49, 111, 71, 150, 29, 116, 20, 136, 186, 174, 191, 8, 40, 146, 135, 94, 143, 145, 79, 1, 122, 39, 196, 194, 70, 46, 50, 158, 53, 165, 167, 148, 189, 119, 140, 4, 12, 14, 173, 44, 64, 166, 184, 153, 171, 32, 188, 144, 190, 35, 154, 121, 25, 54, 134, 102, 55, 168, 139, 155, 132, 183, 201, 178, 159, 27, 57, 72, 109, 107, 65, 104, 209, 51, 47, 200, 60, 75, 22, 120, 69, 31, 83, 76, 118, 24, 131, 5, 84, 81, 105, 125, 208, 88, 95, 13, 82, 78, 0]], Length: 211\n",
      "Robot Routes: [[[149, 137, 98, 123, 18, 115, 43, 6, 73, 130, 36, 21], [200, 60, 75, 22, 120, 69, 31, 83, 76, 118, 24, 131], [167, 148, 189, 119, 140, 4, 12, 14, 173, 44, 64, 166], [187, 74, 96, 114, 85, 113, 185, 164, 112, 87, 80, 138], [79, 1, 122, 39, 196, 194, 70, 46, 50, 158, 53, 165], [71, 150, 29, 116, 20, 136, 186, 174, 191, 8, 40, 146], [197, 199, 161, 205, 19, 179, 198, 124, 92, 59, 110, 103], [206, 90, 157, 11, 61, 30, 3, 177, 16, 172, 62, 127]]]\n",
      "Route: [0, 9, 180, 202, 149, 21, 67, 206, 127, 126, 34, 15, 182, 117, 108, 48, 129, 176, 192, 133, 147, 141, 128, 163, 93, 38, 86, 99, 23, 162, 33, 7, 77, 42, 142, 156, 195, 106, 181, 197, 103, 45, 17, 52, 56, 101, 37, 207, 63, 169, 66, 187, 138, 41, 152, 28, 58, 2, 10, 91, 160, 151, 204, 26, 97, 170, 203, 68, 193, 89, 100, 175, 49, 111, 71, 146, 135, 94, 143, 145, 79, 165, 167, 166, 184, 153, 171, 32, 188, 144, 190, 35, 154, 121, 25, 54, 134, 102, 55, 168, 139, 155, 132, 183, 201, 178, 159, 27, 57, 72, 109, 107, 65, 104, 209, 51, 47, 200, 131, 5, 84, 81, 105, 125, 208, 88, 95, 13, 82, 78, 0], Robot Group: [[149, 137, 98, 123, 18, 115, 43, 6, 73, 130, 36, 21], [200, 60, 75, 22, 120, 69, 31, 83, 76, 118, 24, 131], [167, 148, 189, 119, 140, 4, 12, 14, 173, 44, 64, 166], [187, 74, 96, 114, 85, 113, 185, 164, 112, 87, 80, 138], [79, 1, 122, 39, 196, 194, 70, 46, 50, 158, 53, 165], [71, 150, 29, 116, 20, 136, 186, 174, 191, 8, 40, 146], [197, 199, 161, 205, 19, 179, 198, 124, 92, 59, 110, 103], [206, 90, 157, 11, 61, 30, 3, 177, 16, 172, 62, 127]]\n",
      "Vehicle 0: 60652 m, 365.931 min, including 45.279 mins waiting time.\n",
      "Total distance of all routes: : 60652 m\n",
      "Maximum travel time: 365.931 min\n",
      "VRP-RD\n",
      "Routes: [[0, 9, 180, 202, 149, 137, 98, 123, 18, 115, 43, 6, 73, 130, 36, 21, 67, 206, 90, 157, 11, 61, 30, 3, 177, 16, 172, 62, 127, 126, 34, 15, 182, 117, 108, 48, 129, 176, 192, 133, 147, 141, 128, 163, 93, 38, 86, 99, 23, 162, 33, 7, 77, 42, 142, 156, 195, 106, 181, 197, 199, 161, 205, 19, 179, 198, 124, 92, 59, 110, 103, 45, 17, 52, 56, 101, 37, 207, 63, 169, 66, 187, 74, 96, 114, 85, 113, 185, 164, 112, 87, 80, 138, 41, 152, 28, 58, 2, 10, 91, 160, 151, 204, 26, 97, 170, 203, 68, 193, 89, 100, 175, 49, 111, 71, 150, 29, 116, 20, 136, 186, 174, 191, 8, 40, 146, 135, 94, 143, 145, 79, 1, 122, 39, 196, 194, 70, 46, 50, 158, 53, 165, 167, 148, 189, 119, 140, 4, 12, 14, 173, 44, 64, 166, 184, 153, 171, 32, 188, 144, 190, 35, 154, 121, 25, 54, 134, 102, 55, 168, 139, 155, 132, 183, 201, 178, 159, 27, 57, 72, 109, 107, 65, 104, 209, 51, 47, 200, 60, 75, 22, 120, 69, 31, 83, 76, 118, 24, 131, 5, 84, 81, 105, 125, 208, 88, 95, 13, 82, 78, 0]], Length: 211\n",
      "Robot Routes: [[[149, 137, 98, 123, 18, 115, 43, 6, 73, 130, 36, 21], [200, 60, 75, 22, 120, 69, 31, 83, 76, 118, 24, 131], [167, 148, 189, 119, 140, 4, 12, 14, 173, 44, 64, 166], [187, 74, 96, 114, 85, 113, 185, 164, 112, 87, 80, 138], [79, 1, 122, 39, 196, 194, 70, 46, 50, 158, 53, 165], [71, 150, 29, 116, 20, 136, 186, 174, 191, 8, 40, 146], [197, 199, 161, 205, 19, 179, 198, 124, 92, 59, 110, 103], [206, 90, 157, 11, 61, 30, 3, 177, 16, 172, 62, 127]]]\n",
      "Route: [0, 9, 180, 202, 149, 21, 67, 206, 127, 126, 34, 15, 182, 117, 108, 48, 129, 176, 192, 133, 147, 141, 128, 163, 93, 38, 86, 99, 23, 162, 33, 7, 77, 42, 142, 156, 195, 106, 181, 197, 103, 45, 17, 52, 56, 101, 37, 207, 63, 169, 66, 187, 138, 41, 152, 28, 58, 2, 10, 91, 160, 151, 204, 26, 97, 170, 203, 68, 193, 89, 100, 175, 49, 111, 71, 146, 135, 94, 143, 145, 79, 165, 167, 166, 184, 153, 171, 32, 188, 144, 190, 35, 154, 121, 25, 54, 134, 102, 55, 168, 139, 155, 132, 183, 201, 178, 159, 27, 57, 72, 109, 107, 65, 104, 209, 51, 47, 200, 131, 5, 84, 81, 105, 125, 208, 88, 95, 13, 82, 78, 0], Robot Group: [[149, 137, 98, 123, 18, 115, 43, 6, 73, 130, 36, 21], [200, 60, 75, 22, 120, 69, 31, 83, 76, 118, 24, 131], [167, 148, 189, 119, 140, 4, 12, 14, 173, 44, 64, 166], [187, 74, 96, 114, 85, 113, 185, 164, 112, 87, 80, 138], [79, 1, 122, 39, 196, 194, 70, 46, 50, 158, 53, 165], [71, 150, 29, 116, 20, 136, 186, 174, 191, 8, 40, 146], [197, 199, 161, 205, 19, 179, 198, 124, 92, 59, 110, 103], [206, 90, 157, 11, 61, 30, 3, 177, 16, 172, 62, 127]]\n",
      "Vehicle 0: 58543 m, 352.055 min, including 53.512 mins waiting time.\n",
      "Total distance of all routes: : 58543 m\n",
      "Maximum travel time: 352.055 min\n",
      "Trial 7...\n",
      "VRP\n",
      "Routes: [[0, 189, 86, 72, 54, 159, 160, 28, 123, 206, 192, 119, 121, 82, 35, 49, 148, 103, 74, 64, 134, 101, 127, 42, 187, 205, 120, 2, 84, 17, 21, 115, 40, 38, 149, 178, 99, 47, 146, 69, 128, 93, 163, 53, 168, 185, 77, 153, 111, 92, 193, 100, 43, 95, 155, 110, 29, 94, 36, 8, 32, 142, 71, 46, 207, 5, 122, 67, 196, 176, 1, 184, 109, 27, 50, 14, 59, 131, 171, 52, 133, 130, 139, 166, 26, 85, 4, 66, 91, 201, 190, 186, 105, 83, 203, 51, 6, 154, 124, 112, 132, 76, 60, 25, 10, 88, 208, 198, 188, 151, 200, 12, 191, 89, 179, 41, 18, 195, 22, 78, 102, 39, 156, 145, 182, 55, 117, 75, 141, 45, 13, 175, 180, 3, 136, 172, 106, 63, 97, 157, 30, 20, 31, 164, 56, 204, 181, 70, 126, 137, 61, 65, 23, 87, 170, 162, 37, 33, 144, 194, 116, 98, 158, 48, 140, 9, 183, 114, 118, 150, 152, 11, 96, 79, 197, 80, 108, 90, 44, 165, 62, 7, 129, 104, 135, 202, 169, 58, 68, 209, 174, 19, 177, 113, 167, 199, 125, 147, 143, 15, 57, 24, 138, 73, 107, 34, 81, 16, 161, 173, 0]], Length: 211\n",
      "Vehicle 0: 69337 m, 489.337 min, including 0 mins waiting time.\n",
      "Total distance of all routes: : 69337 m\n",
      "Maximum travel time: 489.337 min\n",
      "VRP-D\n",
      "Routes: [[0, 189, 86, 72, 54, 159, 160, 28, 123, 206, 192, 119, 121, 82, 35, 49, 148, 103, 74, 64, 134, 101, 127, 42, 187, 205, 120, 2, 84, 17, 21, 115, 40, 38, 149, 178, 99, 47, 146, 69, 128, 93, 163, 53, 168, 185, 77, 153, 111, 92, 193, 100, 43, 95, 155, 110, 29, 94, 36, 8, 32, 142, 71, 46, 207, 5, 122, 67, 196, 176, 1, 184, 109, 27, 50, 14, 59, 131, 171, 52, 133, 130, 139, 166, 26, 85, 4, 66, 91, 201, 190, 186, 105, 83, 203, 51, 6, 154, 124, 112, 132, 76, 60, 25, 10, 88, 208, 198, 188, 151, 200, 12, 191, 89, 179, 41, 18, 195, 22, 78, 102, 39, 156, 145, 182, 55, 117, 75, 141, 45, 13, 175, 180, 3, 136, 172, 106, 63, 97, 157, 30, 20, 31, 164, 56, 204, 181, 70, 126, 137, 61, 65, 23, 87, 170, 162, 37, 33, 144, 194, 116, 98, 158, 48, 140, 9, 183, 114, 118, 150, 152, 11, 96, 79, 197, 80, 108, 90, 44, 165, 62, 7, 129, 104, 135, 202, 169, 58, 68, 209, 174, 19, 177, 113, 167, 199, 125, 147, 143, 15, 57, 24, 138, 73, 107, 34, 81, 16, 161, 173, 0]], Length: 211\n",
      "Vehicle 0: 65900 m, 465.849 min, including 13.949 mins waiting time.\n",
      "Total distance of all routes: : 65900 m\n",
      "Maximum travel time: 465.849 min\n",
      "VRP-R\n",
      "Routes: [[0, 189, 86, 72, 54, 159, 160, 28, 123, 206, 192, 119, 121, 82, 35, 49, 148, 103, 74, 64, 134, 101, 127, 42, 187, 205, 120, 2, 84, 17, 21, 115, 40, 38, 149, 178, 99, 47, 146, 69, 128, 93, 163, 53, 168, 185, 77, 153, 111, 92, 193, 100, 43, 95, 155, 110, 29, 94, 36, 8, 32, 142, 71, 46, 207, 5, 122, 67, 196, 176, 1, 184, 109, 27, 50, 14, 59, 131, 171, 52, 133, 130, 139, 166, 26, 85, 4, 66, 91, 201, 190, 186, 105, 83, 203, 51, 6, 154, 124, 112, 132, 76, 60, 25, 10, 88, 208, 198, 188, 151, 200, 12, 191, 89, 179, 41, 18, 195, 22, 78, 102, 39, 156, 145, 182, 55, 117, 75, 141, 45, 13, 175, 180, 3, 136, 172, 106, 63, 97, 157, 30, 20, 31, 164, 56, 204, 181, 70, 126, 137, 61, 65, 23, 87, 170, 162, 37, 33, 144, 194, 116, 98, 158, 48, 140, 9, 183, 114, 118, 150, 152, 11, 96, 79, 197, 80, 108, 90, 44, 165, 62, 7, 129, 104, 135, 202, 169, 58, 68, 209, 174, 19, 177, 113, 167, 199, 125, 147, 143, 15, 57, 24, 138, 73, 107, 34, 81, 16, 161, 173, 0]], Length: 211\n",
      "Robot Routes: [[[27, 50, 14, 59, 131, 171, 52, 133, 130, 139, 166, 26], [199, 125, 147, 143, 15, 57, 24, 138, 73, 107, 34, 81], [168, 185, 77, 153, 111, 92, 193, 100, 43, 95, 155, 110], [116, 98, 158, 48, 140, 9, 183, 114, 118, 150, 152, 11], [82, 35, 49, 148, 103, 74, 64, 134, 101, 127, 42, 187], [31, 164, 56, 204, 181, 70, 126, 137, 61, 65, 23, 87]]]\n",
      "Route: [0, 189, 86, 72, 54, 159, 160, 28, 123, 206, 192, 119, 121, 82, 187, 205, 120, 2, 84, 17, 21, 115, 40, 38, 149, 178, 99, 47, 146, 69, 128, 93, 163, 53, 168, 110, 29, 94, 36, 8, 32, 142, 71, 46, 207, 5, 122, 67, 196, 176, 1, 184, 109, 27, 26, 85, 4, 66, 91, 201, 190, 186, 105, 83, 203, 51, 6, 154, 124, 112, 132, 76, 60, 25, 10, 88, 208, 198, 188, 151, 200, 12, 191, 89, 179, 41, 18, 195, 22, 78, 102, 39, 156, 145, 182, 55, 117, 75, 141, 45, 13, 175, 180, 3, 136, 172, 106, 63, 97, 157, 30, 20, 31, 87, 170, 162, 37, 33, 144, 194, 116, 11, 96, 79, 197, 80, 108, 90, 44, 165, 62, 7, 129, 104, 135, 202, 169, 58, 68, 209, 174, 19, 177, 113, 167, 199, 81, 16, 161, 173, 0], Robot Group: [[27, 50, 14, 59, 131, 171, 52, 133, 130, 139, 166, 26], [199, 125, 147, 143, 15, 57, 24, 138, 73, 107, 34, 81], [168, 185, 77, 153, 111, 92, 193, 100, 43, 95, 155, 110], [116, 98, 158, 48, 140, 9, 183, 114, 118, 150, 152, 11], [82, 35, 49, 148, 103, 74, 64, 134, 101, 127, 42, 187], [31, 164, 56, 204, 181, 70, 126, 137, 61, 65, 23, 87]]\n",
      "Vehicle 0: 62365 m, 385.499 min, including 23.134 mins waiting time.\n",
      "Total distance of all routes: : 62365 m\n",
      "Maximum travel time: 385.499 min\n",
      "VRP-RD\n",
      "Routes: [[0, 189, 86, 72, 54, 159, 160, 28, 123, 206, 192, 119, 121, 82, 35, 49, 148, 103, 74, 64, 134, 101, 127, 42, 187, 205, 120, 2, 84, 17, 21, 115, 40, 38, 149, 178, 99, 47, 146, 69, 128, 93, 163, 53, 168, 185, 77, 153, 111, 92, 193, 100, 43, 95, 155, 110, 29, 94, 36, 8, 32, 142, 71, 46, 207, 5, 122, 67, 196, 176, 1, 184, 109, 27, 50, 14, 59, 131, 171, 52, 133, 130, 139, 166, 26, 85, 4, 66, 91, 201, 190, 186, 105, 83, 203, 51, 6, 154, 124, 112, 132, 76, 60, 25, 10, 88, 208, 198, 188, 151, 200, 12, 191, 89, 179, 41, 18, 195, 22, 78, 102, 39, 156, 145, 182, 55, 117, 75, 141, 45, 13, 175, 180, 3, 136, 172, 106, 63, 97, 157, 30, 20, 31, 164, 56, 204, 181, 70, 126, 137, 61, 65, 23, 87, 170, 162, 37, 33, 144, 194, 116, 98, 158, 48, 140, 9, 183, 114, 118, 150, 152, 11, 96, 79, 197, 80, 108, 90, 44, 165, 62, 7, 129, 104, 135, 202, 169, 58, 68, 209, 174, 19, 177, 113, 167, 199, 125, 147, 143, 15, 57, 24, 138, 73, 107, 34, 81, 16, 161, 173, 0]], Length: 211\n",
      "Robot Routes: [[[27, 50, 14, 59, 131, 171, 52, 133, 130, 139, 166, 26], [199, 125, 147, 143, 15, 57, 24, 138, 73, 107, 34, 81], [168, 185, 77, 153, 111, 92, 193, 100, 43, 95, 155, 110], [116, 98, 158, 48, 140, 9, 183, 114, 118, 150, 152, 11], [82, 35, 49, 148, 103, 74, 64, 134, 101, 127, 42, 187], [31, 164, 56, 204, 181, 70, 126, 137, 61, 65, 23, 87]]]\n",
      "Route: [0, 189, 86, 72, 54, 159, 160, 28, 123, 206, 192, 119, 121, 82, 187, 205, 120, 2, 84, 17, 21, 115, 40, 38, 149, 178, 99, 47, 146, 69, 128, 93, 163, 53, 168, 110, 29, 94, 36, 8, 32, 142, 71, 46, 207, 5, 122, 67, 196, 176, 1, 184, 109, 27, 26, 85, 4, 66, 91, 201, 190, 186, 105, 83, 203, 51, 6, 154, 124, 112, 132, 76, 60, 25, 10, 88, 208, 198, 188, 151, 200, 12, 191, 89, 179, 41, 18, 195, 22, 78, 102, 39, 156, 145, 182, 55, 117, 75, 141, 45, 13, 175, 180, 3, 136, 172, 106, 63, 97, 157, 30, 20, 31, 87, 170, 162, 37, 33, 144, 194, 116, 11, 96, 79, 197, 80, 108, 90, 44, 165, 62, 7, 129, 104, 135, 202, 169, 58, 68, 209, 174, 19, 177, 113, 167, 199, 81, 16, 161, 173, 0], Robot Group: [[27, 50, 14, 59, 131, 171, 52, 133, 130, 139, 166, 26], [199, 125, 147, 143, 15, 57, 24, 138, 73, 107, 34, 81], [168, 185, 77, 153, 111, 92, 193, 100, 43, 95, 155, 110], [116, 98, 158, 48, 140, 9, 183, 114, 118, 150, 152, 11], [82, 35, 49, 148, 103, 74, 64, 134, 101, 127, 42, 187], [31, 164, 56, 204, 181, 70, 126, 137, 61, 65, 23, 87]]\n",
      "Vehicle 0: 59631 m, 371.258 min, including 33.627 mins waiting time.\n",
      "Total distance of all routes: : 59631 m\n",
      "Maximum travel time: 371.258 min\n",
      "Trial 8...\n",
      "VRP\n",
      "Routes: [[0, 194, 98, 12, 17, 166, 147, 84, 28, 88, 11, 1, 62, 8, 44, 64, 50, 140, 106, 73, 156, 21, 149, 129, 85, 120, 121, 66, 37, 115, 34, 82, 13, 200, 135, 184, 29, 107, 79, 31, 196, 38, 157, 89, 150, 193, 176, 170, 148, 3, 41, 94, 57, 182, 122, 53, 116, 6, 45, 18, 139, 104, 124, 160, 204, 123, 126, 10, 158, 125, 27, 136, 111, 152, 43, 112, 199, 100, 60, 93, 162, 72, 63, 209, 205, 20, 134, 33, 46, 25, 185, 99, 137, 96, 48, 14, 186, 47, 102, 167, 52, 197, 74, 90, 68, 201, 24, 155, 56, 154, 179, 114, 22, 71, 144, 189, 81, 146, 103, 183, 70, 5, 208, 19, 108, 203, 180, 51, 49, 117, 91, 39, 95, 132, 101, 141, 142, 26, 174, 143, 175, 76, 168, 97, 173, 161, 172, 78, 86, 131, 118, 163, 36, 32, 190, 35, 191, 165, 178, 23, 16, 109, 58, 195, 4, 59, 83, 151, 75, 113, 67, 40, 128, 55, 133, 153, 105, 202, 110, 9, 130, 207, 164, 119, 69, 127, 187, 92, 87, 169, 171, 54, 159, 188, 30, 15, 138, 77, 2, 177, 192, 65, 7, 42, 145, 80, 198, 181, 61, 206, 0]], Length: 211\n",
      "Vehicle 0: 75185 m, 495.185 min, including 0 mins waiting time.\n",
      "Total distance of all routes: : 75185 m\n",
      "Maximum travel time: 495.185 min\n",
      "VRP-D\n",
      "Routes: [[0, 194, 98, 12, 17, 166, 147, 84, 28, 88, 11, 1, 62, 8, 44, 64, 50, 140, 106, 73, 156, 21, 149, 129, 85, 120, 121, 66, 37, 115, 34, 82, 13, 200, 135, 184, 29, 107, 79, 31, 196, 38, 157, 89, 150, 193, 176, 170, 148, 3, 41, 94, 57, 182, 122, 53, 116, 6, 45, 18, 139, 104, 124, 160, 204, 123, 126, 10, 158, 125, 27, 136, 111, 152, 43, 112, 199, 100, 60, 93, 162, 72, 63, 209, 205, 20, 134, 33, 46, 25, 185, 99, 137, 96, 48, 14, 186, 47, 102, 167, 52, 197, 74, 90, 68, 201, 24, 155, 56, 154, 179, 114, 22, 71, 144, 189, 81, 146, 103, 183, 70, 5, 208, 19, 108, 203, 180, 51, 49, 117, 91, 39, 95, 132, 101, 141, 142, 26, 174, 143, 175, 76, 168, 97, 173, 161, 172, 78, 86, 131, 118, 163, 36, 32, 190, 35, 191, 165, 178, 23, 16, 109, 58, 195, 4, 59, 83, 151, 75, 113, 67, 40, 128, 55, 133, 153, 105, 202, 110, 9, 130, 207, 164, 119, 69, 127, 187, 92, 87, 169, 171, 54, 159, 188, 30, 15, 138, 77, 2, 177, 192, 65, 7, 42, 145, 80, 198, 181, 61, 206, 0]], Length: 211\n",
      "Vehicle 0: 72358 m, 472.473 min, including 12.115 mins waiting time.\n",
      "Total distance of all routes: : 72358 m\n",
      "Maximum travel time: 472.473 min\n",
      "VRP-R\n",
      "Routes: [[0, 194, 98, 12, 17, 166, 147, 84, 28, 88, 11, 1, 62, 8, 44, 64, 50, 140, 106, 73, 156, 21, 149, 129, 85, 120, 121, 66, 37, 115, 34, 82, 13, 200, 135, 184, 29, 107, 79, 31, 196, 38, 157, 89, 150, 193, 176, 170, 148, 3, 41, 94, 57, 182, 122, 53, 116, 6, 45, 18, 139, 104, 124, 160, 204, 123, 126, 10, 158, 125, 27, 136, 111, 152, 43, 112, 199, 100, 60, 93, 162, 72, 63, 209, 205, 20, 134, 33, 46, 25, 185, 99, 137, 96, 48, 14, 186, 47, 102, 167, 52, 197, 74, 90, 68, 201, 24, 155, 56, 154, 179, 114, 22, 71, 144, 189, 81, 146, 103, 183, 70, 5, 208, 19, 108, 203, 180, 51, 49, 117, 91, 39, 95, 132, 101, 141, 142, 26, 174, 143, 175, 76, 168, 97, 173, 161, 172, 78, 86, 131, 118, 163, 36, 32, 190, 35, 191, 165, 178, 23, 16, 109, 58, 195, 4, 59, 83, 151, 75, 113, 67, 40, 128, 55, 133, 153, 105, 202, 110, 9, 130, 207, 164, 119, 69, 127, 187, 92, 87, 169, 171, 54, 159, 188, 30, 15, 138, 77, 2, 177, 192, 65, 7, 42, 145, 80, 198, 181, 61, 206, 0]], Length: 211\n",
      "Robot Routes: [[[109, 58, 195, 4, 59, 83, 151, 75, 113, 67, 40, 128], [34, 82, 13, 200, 135, 184, 29, 107, 79, 31, 196, 38], [8, 44, 64, 50, 140, 106, 73, 156, 21, 149, 129, 85], [159, 188, 30, 15, 138, 77, 2, 177, 192, 65, 7, 42], [3, 41, 94, 57, 182, 122, 53, 116, 6, 45, 18, 139], [205, 20, 134, 33, 46, 25, 185, 99, 137, 96, 48, 14], [0, 194, 98, 12, 17, 166, 147, 84, 28, 88, 11, 1]]]\n",
      "Route: [0, 1, 62, 8, 85, 120, 121, 66, 37, 115, 34, 38, 157, 89, 150, 193, 176, 170, 148, 3, 139, 104, 124, 160, 204, 123, 126, 10, 158, 125, 27, 136, 111, 152, 43, 112, 199, 100, 60, 93, 162, 72, 63, 209, 205, 14, 186, 47, 102, 167, 52, 197, 74, 90, 68, 201, 24, 155, 56, 154, 179, 114, 22, 71, 144, 189, 81, 146, 103, 183, 70, 5, 208, 19, 108, 203, 180, 51, 49, 117, 91, 39, 95, 132, 101, 141, 142, 26, 174, 143, 175, 76, 168, 97, 173, 161, 172, 78, 86, 131, 118, 163, 36, 32, 190, 35, 191, 165, 178, 23, 16, 109, 128, 55, 133, 153, 105, 202, 110, 9, 130, 207, 164, 119, 69, 127, 187, 92, 87, 169, 171, 54, 159, 42, 145, 80, 198, 181, 61, 206, 0], Robot Group: [[109, 58, 195, 4, 59, 83, 151, 75, 113, 67, 40, 128], [34, 82, 13, 200, 135, 184, 29, 107, 79, 31, 196, 38], [8, 44, 64, 50, 140, 106, 73, 156, 21, 149, 129, 85], [159, 188, 30, 15, 138, 77, 2, 177, 192, 65, 7, 42], [3, 41, 94, 57, 182, 122, 53, 116, 6, 45, 18, 139], [205, 20, 134, 33, 46, 25, 185, 99, 137, 96, 48, 14], [0, 194, 98, 12, 17, 166, 147, 84, 28, 88, 11, 1]]\n",
      "Vehicle 0: 64596 m, 407.304 min, including 62.708 mins waiting time.\n",
      "Total distance of all routes: : 64596 m\n",
      "Maximum travel time: 407.304 min\n",
      "VRP-RD\n",
      "Routes: [[0, 194, 98, 12, 17, 166, 147, 84, 28, 88, 11, 1, 62, 8, 44, 64, 50, 140, 106, 73, 156, 21, 149, 129, 85, 120, 121, 66, 37, 115, 34, 82, 13, 200, 135, 184, 29, 107, 79, 31, 196, 38, 157, 89, 150, 193, 176, 170, 148, 3, 41, 94, 57, 182, 122, 53, 116, 6, 45, 18, 139, 104, 124, 160, 204, 123, 126, 10, 158, 125, 27, 136, 111, 152, 43, 112, 199, 100, 60, 93, 162, 72, 63, 209, 205, 20, 134, 33, 46, 25, 185, 99, 137, 96, 48, 14, 186, 47, 102, 167, 52, 197, 74, 90, 68, 201, 24, 155, 56, 154, 179, 114, 22, 71, 144, 189, 81, 146, 103, 183, 70, 5, 208, 19, 108, 203, 180, 51, 49, 117, 91, 39, 95, 132, 101, 141, 142, 26, 174, 143, 175, 76, 168, 97, 173, 161, 172, 78, 86, 131, 118, 163, 36, 32, 190, 35, 191, 165, 178, 23, 16, 109, 58, 195, 4, 59, 83, 151, 75, 113, 67, 40, 128, 55, 133, 153, 105, 202, 110, 9, 130, 207, 164, 119, 69, 127, 187, 92, 87, 169, 171, 54, 159, 188, 30, 15, 138, 77, 2, 177, 192, 65, 7, 42, 145, 80, 198, 181, 61, 206, 0]], Length: 211\n",
      "Robot Routes: [[[109, 58, 195, 4, 59, 83, 151, 75, 113, 67, 40, 128], [34, 82, 13, 200, 135, 184, 29, 107, 79, 31, 196, 38], [8, 44, 64, 50, 140, 106, 73, 156, 21, 149, 129, 85], [159, 188, 30, 15, 138, 77, 2, 177, 192, 65, 7, 42], [3, 41, 94, 57, 182, 122, 53, 116, 6, 45, 18, 139], [205, 20, 134, 33, 46, 25, 185, 99, 137, 96, 48, 14], [0, 194, 98, 12, 17, 166, 147, 84, 28, 88, 11, 1]]]\n",
      "Route: [0, 1, 62, 8, 85, 120, 121, 66, 37, 115, 34, 38, 157, 89, 150, 193, 176, 170, 148, 3, 139, 104, 124, 160, 204, 123, 126, 10, 158, 125, 27, 136, 111, 152, 43, 112, 199, 100, 60, 93, 162, 72, 63, 209, 205, 14, 186, 47, 102, 167, 52, 197, 74, 90, 68, 201, 24, 155, 56, 154, 179, 114, 22, 71, 144, 189, 81, 146, 103, 183, 70, 5, 208, 19, 108, 203, 180, 51, 49, 117, 91, 39, 95, 132, 101, 141, 142, 26, 174, 143, 175, 76, 168, 97, 173, 161, 172, 78, 86, 131, 118, 163, 36, 32, 190, 35, 191, 165, 178, 23, 16, 109, 128, 55, 133, 153, 105, 202, 110, 9, 130, 207, 164, 119, 69, 127, 187, 92, 87, 169, 171, 54, 159, 42, 145, 80, 198, 181, 61, 206, 0], Robot Group: [[109, 58, 195, 4, 59, 83, 151, 75, 113, 67, 40, 128], [34, 82, 13, 200, 135, 184, 29, 107, 79, 31, 196, 38], [8, 44, 64, 50, 140, 106, 73, 156, 21, 149, 129, 85], [159, 188, 30, 15, 138, 77, 2, 177, 192, 65, 7, 42], [3, 41, 94, 57, 182, 122, 53, 116, 6, 45, 18, 139], [205, 20, 134, 33, 46, 25, 185, 99, 137, 96, 48, 14], [0, 194, 98, 12, 17, 166, 147, 84, 28, 88, 11, 1]]\n",
      "Vehicle 0: 62013 m, 395.426 min, including 75.413 mins waiting time.\n",
      "Total distance of all routes: : 62013 m\n",
      "Maximum travel time: 395.426 min\n",
      "Trial 9...\n",
      "VRP\n",
      "Routes: [[0, 154, 199, 12, 94, 171, 25, 93, 40, 128, 10, 43, 127, 119, 37, 182, 7, 67, 44, 201, 15, 81, 190, 131, 45, 86, 158, 87, 92, 84, 102, 193, 34, 3, 122, 82, 2, 203, 135, 16, 49, 165, 39, 191, 179, 144, 27, 58, 85, 196, 23, 111, 100, 187, 118, 78, 116, 155, 173, 48, 134, 63, 21, 209, 19, 29, 172, 123, 138, 126, 198, 11, 64, 59, 110, 147, 170, 184, 50, 186, 57, 1, 174, 161, 104, 55, 140, 13, 41, 98, 162, 204, 99, 152, 151, 14, 97, 107, 103, 18, 164, 117, 56, 202, 88, 207, 51, 60, 175, 124, 101, 148, 137, 169, 129, 176, 6, 181, 73, 132, 42, 75, 96, 77, 79, 145, 8, 200, 53, 194, 26, 185, 136, 143, 195, 149, 208, 76, 72, 133, 46, 30, 20, 17, 168, 4, 167, 166, 178, 47, 35, 130, 205, 71, 120, 150, 65, 206, 156, 52, 66, 61, 115, 160, 9, 62, 106, 188, 38, 105, 31, 91, 141, 69, 112, 121, 189, 146, 95, 180, 113, 177, 157, 153, 142, 125, 28, 33, 36, 108, 89, 163, 83, 32, 80, 68, 114, 183, 159, 24, 90, 5, 139, 54, 197, 109, 74, 192, 70, 22, 0]], Length: 211\n",
      "Vehicle 0: 70390 m, 490.39 min, including 0 mins waiting time.\n",
      "Total distance of all routes: : 70390 m\n",
      "Maximum travel time: 490.39 min\n",
      "VRP-D\n",
      "Routes: [[0, 154, 199, 12, 94, 171, 25, 93, 40, 128, 10, 43, 127, 119, 37, 182, 7, 67, 44, 201, 15, 81, 190, 131, 45, 86, 158, 87, 92, 84, 102, 193, 34, 3, 122, 82, 2, 203, 135, 16, 49, 165, 39, 191, 179, 144, 27, 58, 85, 196, 23, 111, 100, 187, 118, 78, 116, 155, 173, 48, 134, 63, 21, 209, 19, 29, 172, 123, 138, 126, 198, 11, 64, 59, 110, 147, 170, 184, 50, 186, 57, 1, 174, 161, 104, 55, 140, 13, 41, 98, 162, 204, 99, 152, 151, 14, 97, 107, 103, 18, 164, 117, 56, 202, 88, 207, 51, 60, 175, 124, 101, 148, 137, 169, 129, 176, 6, 181, 73, 132, 42, 75, 96, 77, 79, 145, 8, 200, 53, 194, 26, 185, 136, 143, 195, 149, 208, 76, 72, 133, 46, 30, 20, 17, 168, 4, 167, 166, 178, 47, 35, 130, 205, 71, 120, 150, 65, 206, 156, 52, 66, 61, 115, 160, 9, 62, 106, 188, 38, 105, 31, 91, 141, 69, 112, 121, 189, 146, 95, 180, 113, 177, 157, 153, 142, 125, 28, 33, 36, 108, 89, 163, 83, 32, 80, 68, 114, 183, 159, 24, 90, 5, 139, 54, 197, 109, 74, 192, 70, 22, 0]], Length: 211\n",
      "Vehicle 0: 68492 m, 469.926 min, including 11.434 mins waiting time.\n",
      "Total distance of all routes: : 68492 m\n",
      "Maximum travel time: 469.926 min\n",
      "VRP-R\n",
      "Routes: [[0, 154, 199, 12, 94, 171, 25, 93, 40, 128, 10, 43, 127, 119, 37, 182, 7, 67, 44, 201, 15, 81, 190, 131, 45, 86, 158, 87, 92, 84, 102, 193, 34, 3, 122, 82, 2, 203, 135, 16, 49, 165, 39, 191, 179, 144, 27, 58, 85, 196, 23, 111, 100, 187, 118, 78, 116, 155, 173, 48, 134, 63, 21, 209, 19, 29, 172, 123, 138, 126, 198, 11, 64, 59, 110, 147, 170, 184, 50, 186, 57, 1, 174, 161, 104, 55, 140, 13, 41, 98, 162, 204, 99, 152, 151, 14, 97, 107, 103, 18, 164, 117, 56, 202, 88, 207, 51, 60, 175, 124, 101, 148, 137, 169, 129, 176, 6, 181, 73, 132, 42, 75, 96, 77, 79, 145, 8, 200, 53, 194, 26, 185, 136, 143, 195, 149, 208, 76, 72, 133, 46, 30, 20, 17, 168, 4, 167, 166, 178, 47, 35, 130, 205, 71, 120, 150, 65, 206, 156, 52, 66, 61, 115, 160, 9, 62, 106, 188, 38, 105, 31, 91, 141, 69, 112, 121, 189, 146, 95, 180, 113, 177, 157, 153, 142, 125, 28, 33, 36, 108, 89, 163, 83, 32, 80, 68, 114, 183, 159, 24, 90, 5, 139, 54, 197, 109, 74, 192, 70, 22, 0]], Length: 211\n",
      "Robot Routes: [[[79, 145, 8, 200, 53, 194, 26, 185, 136, 143, 195, 149], [154, 199, 12, 94, 171, 25, 93, 40, 128, 10, 43, 127], [32, 80, 68, 114, 183, 159, 24, 90, 5, 139, 54, 197], [41, 98, 162, 204, 99, 152, 151, 14, 97, 107, 103, 18], [27, 58, 85, 196, 23, 111, 100, 187, 118, 78, 116, 155], [173, 48, 134, 63, 21, 209, 19, 29, 172, 123, 138, 126], [64, 59, 110, 147, 170, 184, 50, 186, 57, 1, 174, 161], [119, 37, 182, 7, 67, 44, 201, 15, 81, 190, 131, 45]]]\n",
      "Route: [0, 154, 127, 119, 45, 86, 158, 87, 92, 84, 102, 193, 34, 3, 122, 82, 2, 203, 135, 16, 49, 165, 39, 191, 179, 144, 27, 155, 173, 126, 198, 11, 64, 161, 104, 55, 140, 13, 41, 18, 164, 117, 56, 202, 88, 207, 51, 60, 175, 124, 101, 148, 137, 169, 129, 176, 6, 181, 73, 132, 42, 75, 96, 77, 79, 149, 208, 76, 72, 133, 46, 30, 20, 17, 168, 4, 167, 166, 178, 47, 35, 130, 205, 71, 120, 150, 65, 206, 156, 52, 66, 61, 115, 160, 9, 62, 106, 188, 38, 105, 31, 91, 141, 69, 112, 121, 189, 146, 95, 180, 113, 177, 157, 153, 142, 125, 28, 33, 36, 108, 89, 163, 83, 32, 197, 109, 74, 192, 70, 22, 0], Robot Group: [[79, 145, 8, 200, 53, 194, 26, 185, 136, 143, 195, 149], [154, 199, 12, 94, 171, 25, 93, 40, 128, 10, 43, 127], [32, 80, 68, 114, 183, 159, 24, 90, 5, 139, 54, 197], [41, 98, 162, 204, 99, 152, 151, 14, 97, 107, 103, 18], [27, 58, 85, 196, 23, 111, 100, 187, 118, 78, 116, 155], [173, 48, 134, 63, 21, 209, 19, 29, 172, 123, 138, 126], [64, 59, 110, 147, 170, 184, 50, 186, 57, 1, 174, 161], [119, 37, 182, 7, 67, 44, 201, 15, 81, 190, 131, 45]]\n",
      "Vehicle 0: 58494 m, 376.077 min, including 57.583 mins waiting time.\n",
      "Total distance of all routes: : 58494 m\n",
      "Maximum travel time: 376.077 min\n",
      "VRP-RD\n",
      "Routes: [[0, 154, 199, 12, 94, 171, 25, 93, 40, 128, 10, 43, 127, 119, 37, 182, 7, 67, 44, 201, 15, 81, 190, 131, 45, 86, 158, 87, 92, 84, 102, 193, 34, 3, 122, 82, 2, 203, 135, 16, 49, 165, 39, 191, 179, 144, 27, 58, 85, 196, 23, 111, 100, 187, 118, 78, 116, 155, 173, 48, 134, 63, 21, 209, 19, 29, 172, 123, 138, 126, 198, 11, 64, 59, 110, 147, 170, 184, 50, 186, 57, 1, 174, 161, 104, 55, 140, 13, 41, 98, 162, 204, 99, 152, 151, 14, 97, 107, 103, 18, 164, 117, 56, 202, 88, 207, 51, 60, 175, 124, 101, 148, 137, 169, 129, 176, 6, 181, 73, 132, 42, 75, 96, 77, 79, 145, 8, 200, 53, 194, 26, 185, 136, 143, 195, 149, 208, 76, 72, 133, 46, 30, 20, 17, 168, 4, 167, 166, 178, 47, 35, 130, 205, 71, 120, 150, 65, 206, 156, 52, 66, 61, 115, 160, 9, 62, 106, 188, 38, 105, 31, 91, 141, 69, 112, 121, 189, 146, 95, 180, 113, 177, 157, 153, 142, 125, 28, 33, 36, 108, 89, 163, 83, 32, 80, 68, 114, 183, 159, 24, 90, 5, 139, 54, 197, 109, 74, 192, 70, 22, 0]], Length: 211\n",
      "Robot Routes: [[[79, 145, 8, 200, 53, 194, 26, 185, 136, 143, 195, 149], [154, 199, 12, 94, 171, 25, 93, 40, 128, 10, 43, 127], [32, 80, 68, 114, 183, 159, 24, 90, 5, 139, 54, 197], [41, 98, 162, 204, 99, 152, 151, 14, 97, 107, 103, 18], [27, 58, 85, 196, 23, 111, 100, 187, 118, 78, 116, 155], [173, 48, 134, 63, 21, 209, 19, 29, 172, 123, 138, 126], [64, 59, 110, 147, 170, 184, 50, 186, 57, 1, 174, 161], [119, 37, 182, 7, 67, 44, 201, 15, 81, 190, 131, 45]]]\n",
      "Route: [0, 154, 127, 119, 45, 86, 158, 87, 92, 84, 102, 193, 34, 3, 122, 82, 2, 203, 135, 16, 49, 165, 39, 191, 179, 144, 27, 155, 173, 126, 198, 11, 64, 161, 104, 55, 140, 13, 41, 18, 164, 117, 56, 202, 88, 207, 51, 60, 175, 124, 101, 148, 137, 169, 129, 176, 6, 181, 73, 132, 42, 75, 96, 77, 79, 149, 208, 76, 72, 133, 46, 30, 20, 17, 168, 4, 167, 166, 178, 47, 35, 130, 205, 71, 120, 150, 65, 206, 156, 52, 66, 61, 115, 160, 9, 62, 106, 188, 38, 105, 31, 91, 141, 69, 112, 121, 189, 146, 95, 180, 113, 177, 157, 153, 142, 125, 28, 33, 36, 108, 89, 163, 83, 32, 197, 109, 74, 192, 70, 22, 0], Robot Group: [[79, 145, 8, 200, 53, 194, 26, 185, 136, 143, 195, 149], [154, 199, 12, 94, 171, 25, 93, 40, 128, 10, 43, 127], [32, 80, 68, 114, 183, 159, 24, 90, 5, 139, 54, 197], [41, 98, 162, 204, 99, 152, 151, 14, 97, 107, 103, 18], [27, 58, 85, 196, 23, 111, 100, 187, 118, 78, 116, 155], [173, 48, 134, 63, 21, 209, 19, 29, 172, 123, 138, 126], [64, 59, 110, 147, 170, 184, 50, 186, 57, 1, 174, 161], [119, 37, 182, 7, 67, 44, 201, 15, 81, 190, 131, 45]]\n",
      "Vehicle 0: 56347 m, 366.592 min, including 70.245 mins waiting time.\n",
      "Total distance of all routes: : 56347 m\n",
      "Maximum travel time: 366.592 min\n",
      "Trial 10...\n",
      "VRP\n",
      "Routes: [[0, 141, 165, 105, 66, 52, 140, 16, 39, 97, 22, 192, 208, 87, 12, 71, 95, 160, 82, 37, 186, 182, 3, 89, 45, 161, 1, 38, 136, 193, 189, 154, 57, 51, 173, 42, 29, 202, 156, 145, 153, 8, 143, 55, 139, 183, 171, 107, 40, 127, 47, 157, 118, 63, 112, 198, 132, 62, 150, 46, 90, 129, 27, 43, 56, 117, 100, 98, 174, 144, 207, 184, 35, 72, 53, 58, 31, 48, 103, 196, 4, 138, 111, 6, 26, 14, 133, 104, 101, 68, 142, 166, 20, 179, 209, 73, 18, 50, 120, 124, 75, 93, 106, 148, 200, 94, 76, 109, 172, 102, 158, 146, 187, 185, 116, 19, 149, 162, 135, 128, 188, 205, 181, 151, 164, 86, 170, 113, 61, 92, 194, 41, 167, 7, 175, 36, 130, 10, 25, 44, 177, 28, 123, 65, 15, 24, 67, 81, 155, 125, 206, 131, 137, 180, 21, 204, 197, 80, 64, 23, 159, 74, 30, 9, 77, 176, 108, 201, 34, 168, 54, 13, 32, 152, 17, 70, 69, 96, 91, 85, 60, 203, 121, 147, 195, 122, 191, 84, 59, 134, 114, 169, 178, 190, 5, 49, 126, 119, 78, 110, 33, 163, 11, 2, 79, 199, 88, 115, 83, 99, 0]], Length: 211\n",
      "Vehicle 0: 73408 m, 493.408 min, including 0 mins waiting time.\n",
      "Total distance of all routes: : 73408 m\n",
      "Maximum travel time: 493.408 min\n",
      "VRP-D\n",
      "Routes: [[0, 141, 165, 105, 66, 52, 140, 16, 39, 97, 22, 192, 208, 87, 12, 71, 95, 160, 82, 37, 186, 182, 3, 89, 45, 161, 1, 38, 136, 193, 189, 154, 57, 51, 173, 42, 29, 202, 156, 145, 153, 8, 143, 55, 139, 183, 171, 107, 40, 127, 47, 157, 118, 63, 112, 198, 132, 62, 150, 46, 90, 129, 27, 43, 56, 117, 100, 98, 174, 144, 207, 184, 35, 72, 53, 58, 31, 48, 103, 196, 4, 138, 111, 6, 26, 14, 133, 104, 101, 68, 142, 166, 20, 179, 209, 73, 18, 50, 120, 124, 75, 93, 106, 148, 200, 94, 76, 109, 172, 102, 158, 146, 187, 185, 116, 19, 149, 162, 135, 128, 188, 205, 181, 151, 164, 86, 170, 113, 61, 92, 194, 41, 167, 7, 175, 36, 130, 10, 25, 44, 177, 28, 123, 65, 15, 24, 67, 81, 155, 125, 206, 131, 137, 180, 21, 204, 197, 80, 64, 23, 159, 74, 30, 9, 77, 176, 108, 201, 34, 168, 54, 13, 32, 152, 17, 70, 69, 96, 91, 85, 60, 203, 121, 147, 195, 122, 191, 84, 59, 134, 114, 169, 178, 190, 5, 49, 126, 119, 78, 110, 33, 163, 11, 2, 79, 199, 88, 115, 83, 99, 0]], Length: 211\n",
      "Vehicle 0: 70838 m, 470.469 min, including 13.631 mins waiting time.\n",
      "Total distance of all routes: : 70838 m\n",
      "Maximum travel time: 470.469 min\n",
      "VRP-R\n",
      "Routes: [[0, 141, 165, 105, 66, 52, 140, 16, 39, 97, 22, 192, 208, 87, 12, 71, 95, 160, 82, 37, 186, 182, 3, 89, 45, 161, 1, 38, 136, 193, 189, 154, 57, 51, 173, 42, 29, 202, 156, 145, 153, 8, 143, 55, 139, 183, 171, 107, 40, 127, 47, 157, 118, 63, 112, 198, 132, 62, 150, 46, 90, 129, 27, 43, 56, 117, 100, 98, 174, 144, 207, 184, 35, 72, 53, 58, 31, 48, 103, 196, 4, 138, 111, 6, 26, 14, 133, 104, 101, 68, 142, 166, 20, 179, 209, 73, 18, 50, 120, 124, 75, 93, 106, 148, 200, 94, 76, 109, 172, 102, 158, 146, 187, 185, 116, 19, 149, 162, 135, 128, 188, 205, 181, 151, 164, 86, 170, 113, 61, 92, 194, 41, 167, 7, 175, 36, 130, 10, 25, 44, 177, 28, 123, 65, 15, 24, 67, 81, 155, 125, 206, 131, 137, 180, 21, 204, 197, 80, 64, 23, 159, 74, 30, 9, 77, 176, 108, 201, 34, 168, 54, 13, 32, 152, 17, 70, 69, 96, 91, 85, 60, 203, 121, 147, 195, 122, 191, 84, 59, 134, 114, 169, 178, 190, 5, 49, 126, 119, 78, 110, 33, 163, 11, 2, 79, 199, 88, 115, 83, 99, 0]], Length: 211\n",
      "Robot Routes: [[[41, 167, 7, 175, 36, 130, 10, 25, 44, 177, 28, 123], [21, 204, 197, 80, 64, 23, 159, 74, 30, 9, 77, 176], [0, 141, 165, 105, 66, 52, 140, 16, 39, 97, 22, 192], [162, 135, 128, 188, 205, 181, 151, 164, 86, 170, 113, 61], [161, 1, 38, 136, 193, 189, 154, 57, 51, 173, 42, 29], [55, 139, 183, 171, 107, 40, 127, 47, 157, 118, 63, 112], [75, 93, 106, 148, 200, 94, 76, 109, 172, 102, 158, 146], [69, 96, 91, 85, 60, 203, 121, 147, 195, 122, 191, 84], [78, 110, 33, 163, 11, 2, 79, 199, 88, 115, 83, 99], [4, 138, 111, 6, 26, 14, 133, 104, 101, 68, 142, 166]]]\n",
      "Route: [0, 192, 208, 87, 12, 71, 95, 160, 82, 37, 186, 182, 3, 89, 45, 161, 29, 202, 156, 145, 153, 8, 143, 55, 112, 198, 132, 62, 150, 46, 90, 129, 27, 43, 56, 117, 100, 98, 174, 144, 207, 184, 35, 72, 53, 58, 31, 48, 103, 196, 4, 166, 20, 179, 209, 73, 18, 50, 120, 124, 75, 146, 187, 185, 116, 19, 149, 162, 61, 92, 194, 41, 123, 65, 15, 24, 67, 81, 155, 125, 206, 131, 137, 180, 21, 176, 108, 201, 34, 168, 54, 13, 32, 152, 17, 70, 69, 84, 59, 134, 114, 169, 178, 190, 5, 49, 126, 119, 78, 99, 0], Robot Group: [[41, 167, 7, 175, 36, 130, 10, 25, 44, 177, 28, 123], [21, 204, 197, 80, 64, 23, 159, 74, 30, 9, 77, 176], [0, 141, 165, 105, 66, 52, 140, 16, 39, 97, 22, 192], [162, 135, 128, 188, 205, 181, 151, 164, 86, 170, 113, 61], [161, 1, 38, 136, 193, 189, 154, 57, 51, 173, 42, 29], [55, 139, 183, 171, 107, 40, 127, 47, 157, 118, 63, 112], [75, 93, 106, 148, 200, 94, 76, 109, 172, 102, 158, 146], [69, 96, 91, 85, 60, 203, 121, 147, 195, 122, 191, 84], [78, 110, 33, 163, 11, 2, 79, 199, 88, 115, 83, 99], [4, 138, 111, 6, 26, 14, 133, 104, 101, 68, 142, 166]]\n",
      "Vehicle 0: 57566 m, 358.276 min, including 80.71 mins waiting time.\n",
      "Total distance of all routes: : 57566 m\n",
      "Maximum travel time: 358.276 min\n",
      "VRP-RD\n",
      "Routes: [[0, 141, 165, 105, 66, 52, 140, 16, 39, 97, 22, 192, 208, 87, 12, 71, 95, 160, 82, 37, 186, 182, 3, 89, 45, 161, 1, 38, 136, 193, 189, 154, 57, 51, 173, 42, 29, 202, 156, 145, 153, 8, 143, 55, 139, 183, 171, 107, 40, 127, 47, 157, 118, 63, 112, 198, 132, 62, 150, 46, 90, 129, 27, 43, 56, 117, 100, 98, 174, 144, 207, 184, 35, 72, 53, 58, 31, 48, 103, 196, 4, 138, 111, 6, 26, 14, 133, 104, 101, 68, 142, 166, 20, 179, 209, 73, 18, 50, 120, 124, 75, 93, 106, 148, 200, 94, 76, 109, 172, 102, 158, 146, 187, 185, 116, 19, 149, 162, 135, 128, 188, 205, 181, 151, 164, 86, 170, 113, 61, 92, 194, 41, 167, 7, 175, 36, 130, 10, 25, 44, 177, 28, 123, 65, 15, 24, 67, 81, 155, 125, 206, 131, 137, 180, 21, 204, 197, 80, 64, 23, 159, 74, 30, 9, 77, 176, 108, 201, 34, 168, 54, 13, 32, 152, 17, 70, 69, 96, 91, 85, 60, 203, 121, 147, 195, 122, 191, 84, 59, 134, 114, 169, 178, 190, 5, 49, 126, 119, 78, 110, 33, 163, 11, 2, 79, 199, 88, 115, 83, 99, 0]], Length: 211\n",
      "Robot Routes: [[[41, 167, 7, 175, 36, 130, 10, 25, 44, 177, 28, 123], [21, 204, 197, 80, 64, 23, 159, 74, 30, 9, 77, 176], [0, 141, 165, 105, 66, 52, 140, 16, 39, 97, 22, 192], [162, 135, 128, 188, 205, 181, 151, 164, 86, 170, 113, 61], [161, 1, 38, 136, 193, 189, 154, 57, 51, 173, 42, 29], [55, 139, 183, 171, 107, 40, 127, 47, 157, 118, 63, 112], [75, 93, 106, 148, 200, 94, 76, 109, 172, 102, 158, 146], [69, 96, 91, 85, 60, 203, 121, 147, 195, 122, 191, 84], [78, 110, 33, 163, 11, 2, 79, 199, 88, 115, 83, 99], [4, 138, 111, 6, 26, 14, 133, 104, 101, 68, 142, 166]]]\n",
      "Route: [0, 192, 208, 87, 12, 71, 95, 160, 82, 37, 186, 182, 3, 89, 45, 161, 29, 202, 156, 145, 153, 8, 143, 55, 112, 198, 132, 62, 150, 46, 90, 129, 27, 43, 56, 117, 100, 98, 174, 144, 207, 184, 35, 72, 53, 58, 31, 48, 103, 196, 4, 166, 20, 179, 209, 73, 18, 50, 120, 124, 75, 146, 187, 185, 116, 19, 149, 162, 61, 92, 194, 41, 123, 65, 15, 24, 67, 81, 155, 125, 206, 131, 137, 180, 21, 176, 108, 201, 34, 168, 54, 13, 32, 152, 17, 70, 69, 84, 59, 134, 114, 169, 178, 190, 5, 49, 126, 119, 78, 99, 0], Robot Group: [[41, 167, 7, 175, 36, 130, 10, 25, 44, 177, 28, 123], [21, 204, 197, 80, 64, 23, 159, 74, 30, 9, 77, 176], [0, 141, 165, 105, 66, 52, 140, 16, 39, 97, 22, 192], [162, 135, 128, 188, 205, 181, 151, 164, 86, 170, 113, 61], [161, 1, 38, 136, 193, 189, 154, 57, 51, 173, 42, 29], [55, 139, 183, 171, 107, 40, 127, 47, 157, 118, 63, 112], [75, 93, 106, 148, 200, 94, 76, 109, 172, 102, 158, 146], [69, 96, 91, 85, 60, 203, 121, 147, 195, 122, 191, 84], [78, 110, 33, 163, 11, 2, 79, 199, 88, 115, 83, 99], [4, 138, 111, 6, 26, 14, 133, 104, 101, 68, 142, 166]]\n",
      "Vehicle 0: 55767 m, 351.53 min, including 93.763 mins waiting time.\n",
      "Total distance of all routes: : 55767 m\n",
      "Maximum travel time: 351.53 min\n",
      "Trial 11...\n",
      "VRP\n",
      "Routes: [[0, 10, 144, 79, 22, 29, 123, 100, 63, 199, 198, 132, 62, 134, 32, 126, 99, 187, 118, 112, 70, 162, 119, 115, 117, 67, 139, 152, 54, 133, 168, 59, 190, 209, 178, 15, 136, 35, 120, 170, 110, 94, 194, 14, 73, 185, 12, 66, 208, 5, 95, 17, 52, 165, 148, 154, 145, 2, 163, 84, 158, 20, 49, 6, 65, 191, 137, 127, 105, 122, 96, 129, 169, 174, 77, 11, 86, 172, 68, 160, 184, 138, 135, 179, 40, 204, 41, 36, 42, 150, 82, 121, 107, 147, 146, 167, 85, 180, 60, 71, 143, 196, 13, 114, 200, 7, 188, 88, 131, 25, 103, 33, 16, 55, 21, 50, 101, 37, 44, 4, 183, 124, 102, 173, 9, 87, 74, 202, 81, 83, 45, 18, 38, 34, 8, 51, 90, 56, 61, 164, 205, 206, 161, 140, 24, 19, 91, 166, 177, 203, 58, 23, 153, 3, 97, 28, 189, 72, 141, 89, 201, 47, 142, 197, 125, 156, 26, 92, 195, 151, 181, 113, 111, 69, 116, 171, 46, 43, 64, 207, 78, 48, 106, 193, 75, 39, 1, 192, 109, 80, 30, 155, 98, 159, 27, 93, 149, 175, 176, 108, 104, 157, 57, 76, 182, 53, 31, 186, 130, 128, 0]], Length: 211\n",
      "Vehicle 0: 71063 m, 491.063 min, including 0 mins waiting time.\n",
      "Total distance of all routes: : 71063 m\n",
      "Maximum travel time: 491.063 min\n",
      "VRP-D\n",
      "Routes: [[0, 10, 144, 79, 22, 29, 123, 100, 63, 199, 198, 132, 62, 134, 32, 126, 99, 187, 118, 112, 70, 162, 119, 115, 117, 67, 139, 152, 54, 133, 168, 59, 190, 209, 178, 15, 136, 35, 120, 170, 110, 94, 194, 14, 73, 185, 12, 66, 208, 5, 95, 17, 52, 165, 148, 154, 145, 2, 163, 84, 158, 20, 49, 6, 65, 191, 137, 127, 105, 122, 96, 129, 169, 174, 77, 11, 86, 172, 68, 160, 184, 138, 135, 179, 40, 204, 41, 36, 42, 150, 82, 121, 107, 147, 146, 167, 85, 180, 60, 71, 143, 196, 13, 114, 200, 7, 188, 88, 131, 25, 103, 33, 16, 55, 21, 50, 101, 37, 44, 4, 183, 124, 102, 173, 9, 87, 74, 202, 81, 83, 45, 18, 38, 34, 8, 51, 90, 56, 61, 164, 205, 206, 161, 140, 24, 19, 91, 166, 177, 203, 58, 23, 153, 3, 97, 28, 189, 72, 141, 89, 201, 47, 142, 197, 125, 156, 26, 92, 195, 151, 181, 113, 111, 69, 116, 171, 46, 43, 64, 207, 78, 48, 106, 193, 75, 39, 1, 192, 109, 80, 30, 155, 98, 159, 27, 93, 149, 175, 176, 108, 104, 157, 57, 76, 182, 53, 31, 186, 130, 128, 0]], Length: 211\n",
      "Vehicle 0: 70303 m, 470.513 min, including 10.21 mins waiting time.\n",
      "Total distance of all routes: : 70303 m\n",
      "Maximum travel time: 470.513 min\n",
      "VRP-R\n",
      "Routes: [[0, 10, 144, 79, 22, 29, 123, 100, 63, 199, 198, 132, 62, 134, 32, 126, 99, 187, 118, 112, 70, 162, 119, 115, 117, 67, 139, 152, 54, 133, 168, 59, 190, 209, 178, 15, 136, 35, 120, 170, 110, 94, 194, 14, 73, 185, 12, 66, 208, 5, 95, 17, 52, 165, 148, 154, 145, 2, 163, 84, 158, 20, 49, 6, 65, 191, 137, 127, 105, 122, 96, 129, 169, 174, 77, 11, 86, 172, 68, 160, 184, 138, 135, 179, 40, 204, 41, 36, 42, 150, 82, 121, 107, 147, 146, 167, 85, 180, 60, 71, 143, 196, 13, 114, 200, 7, 188, 88, 131, 25, 103, 33, 16, 55, 21, 50, 101, 37, 44, 4, 183, 124, 102, 173, 9, 87, 74, 202, 81, 83, 45, 18, 38, 34, 8, 51, 90, 56, 61, 164, 205, 206, 161, 140, 24, 19, 91, 166, 177, 203, 58, 23, 153, 3, 97, 28, 189, 72, 141, 89, 201, 47, 142, 197, 125, 156, 26, 92, 195, 151, 181, 113, 111, 69, 116, 171, 46, 43, 64, 207, 78, 48, 106, 193, 75, 39, 1, 192, 109, 80, 30, 155, 98, 159, 27, 93, 149, 175, 176, 108, 104, 157, 57, 76, 182, 53, 31, 186, 130, 128, 0]], Length: 211\n",
      "Robot Routes: [[[36, 42, 150, 82, 121, 107, 147, 146, 167, 85, 180, 60], [176, 108, 104, 157, 57, 76, 182, 53, 31, 186, 130, 128], [26, 92, 195, 151, 181, 113, 111, 69, 116, 171, 46, 43], [0, 10, 144, 79, 22, 29, 123, 100, 63, 199, 198, 132], [110, 94, 194, 14, 73, 185, 12, 66, 208, 5, 95, 17], [11, 86, 172, 68, 160, 184, 138, 135, 179, 40, 204, 41], [158, 20, 49, 6, 65, 191, 137, 127, 105, 122, 96, 129], [166, 177, 203, 58, 23, 153, 3, 97, 28, 189, 72, 141], [71, 143, 196, 13, 114, 200, 7, 188, 88, 131, 25, 103]]]\n",
      "Route: [0, 132, 62, 134, 32, 126, 99, 187, 118, 112, 70, 162, 119, 115, 117, 67, 139, 152, 54, 133, 168, 59, 190, 209, 178, 15, 136, 35, 120, 170, 110, 17, 52, 165, 148, 154, 145, 2, 163, 84, 158, 129, 169, 174, 77, 11, 41, 36, 60, 71, 103, 33, 16, 55, 21, 50, 101, 37, 44, 4, 183, 124, 102, 173, 9, 87, 74, 202, 81, 83, 45, 18, 38, 34, 8, 51, 90, 56, 61, 164, 205, 206, 161, 140, 24, 19, 91, 166, 141, 89, 201, 47, 142, 197, 125, 156, 26, 43, 64, 207, 78, 48, 106, 193, 75, 39, 1, 192, 109, 80, 30, 155, 98, 159, 27, 93, 149, 175, 176, 128, 0], Robot Group: [[36, 42, 150, 82, 121, 107, 147, 146, 167, 85, 180, 60], [176, 108, 104, 157, 57, 76, 182, 53, 31, 186, 130, 128], [26, 92, 195, 151, 181, 113, 111, 69, 116, 171, 46, 43], [0, 10, 144, 79, 22, 29, 123, 100, 63, 199, 198, 132], [110, 94, 194, 14, 73, 185, 12, 66, 208, 5, 95, 17], [11, 86, 172, 68, 160, 184, 138, 135, 179, 40, 204, 41], [158, 20, 49, 6, 65, 191, 137, 127, 105, 122, 96, 129], [166, 177, 203, 58, 23, 153, 3, 97, 28, 189, 72, 141], [71, 143, 196, 13, 114, 200, 7, 188, 88, 131, 25, 103]]\n",
      "Vehicle 0: 55390 m, 381.642 min, including 86.252 mins waiting time.\n",
      "Total distance of all routes: : 55390 m\n",
      "Maximum travel time: 381.642 min\n",
      "VRP-RD\n",
      "Routes: [[0, 10, 144, 79, 22, 29, 123, 100, 63, 199, 198, 132, 62, 134, 32, 126, 99, 187, 118, 112, 70, 162, 119, 115, 117, 67, 139, 152, 54, 133, 168, 59, 190, 209, 178, 15, 136, 35, 120, 170, 110, 94, 194, 14, 73, 185, 12, 66, 208, 5, 95, 17, 52, 165, 148, 154, 145, 2, 163, 84, 158, 20, 49, 6, 65, 191, 137, 127, 105, 122, 96, 129, 169, 174, 77, 11, 86, 172, 68, 160, 184, 138, 135, 179, 40, 204, 41, 36, 42, 150, 82, 121, 107, 147, 146, 167, 85, 180, 60, 71, 143, 196, 13, 114, 200, 7, 188, 88, 131, 25, 103, 33, 16, 55, 21, 50, 101, 37, 44, 4, 183, 124, 102, 173, 9, 87, 74, 202, 81, 83, 45, 18, 38, 34, 8, 51, 90, 56, 61, 164, 205, 206, 161, 140, 24, 19, 91, 166, 177, 203, 58, 23, 153, 3, 97, 28, 189, 72, 141, 89, 201, 47, 142, 197, 125, 156, 26, 92, 195, 151, 181, 113, 111, 69, 116, 171, 46, 43, 64, 207, 78, 48, 106, 193, 75, 39, 1, 192, 109, 80, 30, 155, 98, 159, 27, 93, 149, 175, 176, 108, 104, 157, 57, 76, 182, 53, 31, 186, 130, 128, 0]], Length: 211\n",
      "Robot Routes: [[[36, 42, 150, 82, 121, 107, 147, 146, 167, 85, 180, 60], [176, 108, 104, 157, 57, 76, 182, 53, 31, 186, 130, 128], [26, 92, 195, 151, 181, 113, 111, 69, 116, 171, 46, 43], [0, 10, 144, 79, 22, 29, 123, 100, 63, 199, 198, 132], [110, 94, 194, 14, 73, 185, 12, 66, 208, 5, 95, 17], [11, 86, 172, 68, 160, 184, 138, 135, 179, 40, 204, 41], [158, 20, 49, 6, 65, 191, 137, 127, 105, 122, 96, 129], [166, 177, 203, 58, 23, 153, 3, 97, 28, 189, 72, 141], [71, 143, 196, 13, 114, 200, 7, 188, 88, 131, 25, 103]]]\n",
      "Route: [0, 132, 62, 134, 32, 126, 99, 187, 118, 112, 70, 162, 119, 115, 117, 67, 139, 152, 54, 133, 168, 59, 190, 209, 178, 15, 136, 35, 120, 170, 110, 17, 52, 165, 148, 154, 145, 2, 163, 84, 158, 129, 169, 174, 77, 11, 41, 36, 60, 71, 103, 33, 16, 55, 21, 50, 101, 37, 44, 4, 183, 124, 102, 173, 9, 87, 74, 202, 81, 83, 45, 18, 38, 34, 8, 51, 90, 56, 61, 164, 205, 206, 161, 140, 24, 19, 91, 166, 141, 89, 201, 47, 142, 197, 125, 156, 26, 43, 64, 207, 78, 48, 106, 193, 75, 39, 1, 192, 109, 80, 30, 155, 98, 159, 27, 93, 149, 175, 176, 128, 0], Robot Group: [[36, 42, 150, 82, 121, 107, 147, 146, 167, 85, 180, 60], [176, 108, 104, 157, 57, 76, 182, 53, 31, 186, 130, 128], [26, 92, 195, 151, 181, 113, 111, 69, 116, 171, 46, 43], [0, 10, 144, 79, 22, 29, 123, 100, 63, 199, 198, 132], [110, 94, 194, 14, 73, 185, 12, 66, 208, 5, 95, 17], [11, 86, 172, 68, 160, 184, 138, 135, 179, 40, 204, 41], [158, 20, 49, 6, 65, 191, 137, 127, 105, 122, 96, 129], [166, 177, 203, 58, 23, 153, 3, 97, 28, 189, 72, 141], [71, 143, 196, 13, 114, 200, 7, 188, 88, 131, 25, 103]]\n",
      "Vehicle 0: 54525 m, 373.398 min, including 96.873 mins waiting time.\n",
      "Total distance of all routes: : 54525 m\n",
      "Maximum travel time: 373.398 min\n",
      "Trial 12...\n",
      "VRP\n",
      "Routes: [[0, 30, 59, 169, 97, 73, 138, 78, 174, 3, 158, 74, 64, 202, 123, 121, 45, 40, 139, 152, 183, 77, 208, 21, 179, 171, 67, 20, 127, 133, 175, 203, 100, 107, 165, 128, 91, 85, 47, 42, 180, 136, 148, 115, 163, 102, 129, 31, 103, 134, 187, 4, 111, 87, 56, 13, 63, 72, 112, 182, 49, 178, 126, 69, 191, 162, 205, 76, 164, 19, 18, 188, 88, 141, 65, 106, 39, 157, 122, 79, 90, 143, 181, 135, 66, 5, 35, 167, 114, 154, 89, 110, 124, 96, 120, 37, 199, 185, 50, 142, 28, 48, 8, 101, 14, 86, 196, 184, 68, 145, 147, 117, 12, 55, 206, 189, 33, 61, 172, 204, 15, 29, 99, 9, 118, 26, 93, 46, 81, 109, 193, 23, 1, 166, 156, 34, 161, 2, 62, 16, 7, 105, 10, 70, 58, 168, 132, 53, 177, 144, 24, 130, 51, 153, 150, 44, 201, 209, 137, 195, 54, 82, 95, 17, 25, 155, 60, 176, 194, 192, 32, 27, 116, 98, 149, 198, 41, 190, 197, 84, 75, 92, 200, 151, 6, 104, 43, 159, 94, 119, 170, 207, 71, 22, 108, 83, 52, 146, 38, 160, 173, 113, 11, 186, 57, 140, 36, 125, 80, 131, 0]], Length: 211\n",
      "Vehicle 0: 71337 m, 491.337 min, including 0 mins waiting time.\n",
      "Total distance of all routes: : 71337 m\n",
      "Maximum travel time: 491.337 min\n",
      "VRP-D\n",
      "Routes: [[0, 30, 59, 169, 97, 73, 138, 78, 174, 3, 158, 74, 64, 202, 123, 121, 45, 40, 139, 152, 183, 77, 208, 21, 179, 171, 67, 20, 127, 133, 175, 203, 100, 107, 165, 128, 91, 85, 47, 42, 180, 136, 148, 115, 163, 102, 129, 31, 103, 134, 187, 4, 111, 87, 56, 13, 63, 72, 112, 182, 49, 178, 126, 69, 191, 162, 205, 76, 164, 19, 18, 188, 88, 141, 65, 106, 39, 157, 122, 79, 90, 143, 181, 135, 66, 5, 35, 167, 114, 154, 89, 110, 124, 96, 120, 37, 199, 185, 50, 142, 28, 48, 8, 101, 14, 86, 196, 184, 68, 145, 147, 117, 12, 55, 206, 189, 33, 61, 172, 204, 15, 29, 99, 9, 118, 26, 93, 46, 81, 109, 193, 23, 1, 166, 156, 34, 161, 2, 62, 16, 7, 105, 10, 70, 58, 168, 132, 53, 177, 144, 24, 130, 51, 153, 150, 44, 201, 209, 137, 195, 54, 82, 95, 17, 25, 155, 60, 176, 194, 192, 32, 27, 116, 98, 149, 198, 41, 190, 197, 84, 75, 92, 200, 151, 6, 104, 43, 159, 94, 119, 170, 207, 71, 22, 108, 83, 52, 146, 38, 160, 173, 113, 11, 186, 57, 140, 36, 125, 80, 131, 0]], Length: 211\n",
      "Vehicle 0: 68952 m, 469.974 min, including 13.022 mins waiting time.\n",
      "Total distance of all routes: : 68952 m\n",
      "Maximum travel time: 469.974 min\n",
      "VRP-R\n",
      "Routes: [[0, 30, 59, 169, 97, 73, 138, 78, 174, 3, 158, 74, 64, 202, 123, 121, 45, 40, 139, 152, 183, 77, 208, 21, 179, 171, 67, 20, 127, 133, 175, 203, 100, 107, 165, 128, 91, 85, 47, 42, 180, 136, 148, 115, 163, 102, 129, 31, 103, 134, 187, 4, 111, 87, 56, 13, 63, 72, 112, 182, 49, 178, 126, 69, 191, 162, 205, 76, 164, 19, 18, 188, 88, 141, 65, 106, 39, 157, 122, 79, 90, 143, 181, 135, 66, 5, 35, 167, 114, 154, 89, 110, 124, 96, 120, 37, 199, 185, 50, 142, 28, 48, 8, 101, 14, 86, 196, 184, 68, 145, 147, 117, 12, 55, 206, 189, 33, 61, 172, 204, 15, 29, 99, 9, 118, 26, 93, 46, 81, 109, 193, 23, 1, 166, 156, 34, 161, 2, 62, 16, 7, 105, 10, 70, 58, 168, 132, 53, 177, 144, 24, 130, 51, 153, 150, 44, 201, 209, 137, 195, 54, 82, 95, 17, 25, 155, 60, 176, 194, 192, 32, 27, 116, 98, 149, 198, 41, 190, 197, 84, 75, 92, 200, 151, 6, 104, 43, 159, 94, 119, 170, 207, 71, 22, 108, 83, 52, 146, 38, 160, 173, 113, 11, 186, 57, 140, 36, 125, 80, 131, 0]], Length: 211\n",
      "Robot Routes: [[[35, 167, 114, 154, 89, 110, 124, 96, 120, 37, 199, 185], [86, 196, 184, 68, 145, 147, 117, 12, 55, 206, 189, 33], [105, 10, 70, 58, 168, 132, 53, 177, 144, 24, 130, 51], [38, 160, 173, 113, 11, 186, 57, 140, 36, 125, 80, 131], [99, 9, 118, 26, 93, 46, 81, 109, 193, 23, 1, 166], [97, 73, 138, 78, 174, 3, 158, 74, 64, 202, 123, 121], [72, 112, 182, 49, 178, 126, 69, 191, 162, 205, 76, 164], [32, 27, 116, 98, 149, 198, 41, 190, 197, 84, 75, 92]]]\n",
      "Route: [0, 30, 59, 169, 97, 121, 45, 40, 139, 152, 183, 77, 208, 21, 179, 171, 67, 20, 127, 133, 175, 203, 100, 107, 165, 128, 91, 85, 47, 42, 180, 136, 148, 115, 163, 102, 129, 31, 103, 134, 187, 4, 111, 87, 56, 13, 63, 72, 164, 19, 18, 188, 88, 141, 65, 106, 39, 157, 122, 79, 90, 143, 181, 135, 66, 5, 35, 185, 50, 142, 28, 48, 8, 101, 14, 86, 33, 61, 172, 204, 15, 29, 99, 166, 156, 34, 161, 2, 62, 16, 7, 105, 51, 153, 150, 44, 201, 209, 137, 195, 54, 82, 95, 17, 25, 155, 60, 176, 194, 192, 32, 92, 200, 151, 6, 104, 43, 159, 94, 119, 170, 207, 71, 22, 108, 83, 52, 146, 38, 131, 0], Robot Group: [[35, 167, 114, 154, 89, 110, 124, 96, 120, 37, 199, 185], [86, 196, 184, 68, 145, 147, 117, 12, 55, 206, 189, 33], [105, 10, 70, 58, 168, 132, 53, 177, 144, 24, 130, 51], [38, 160, 173, 113, 11, 186, 57, 140, 36, 125, 80, 131], [99, 9, 118, 26, 93, 46, 81, 109, 193, 23, 1, 166], [97, 73, 138, 78, 174, 3, 158, 74, 64, 202, 123, 121], [72, 112, 182, 49, 178, 126, 69, 191, 162, 205, 76, 164], [32, 27, 116, 98, 149, 198, 41, 190, 197, 84, 75, 92]]\n",
      "Vehicle 0: 58640 m, 389.939 min, including 71.299 mins waiting time.\n",
      "Total distance of all routes: : 58640 m\n",
      "Maximum travel time: 389.939 min\n",
      "VRP-RD\n",
      "Routes: [[0, 30, 59, 169, 97, 73, 138, 78, 174, 3, 158, 74, 64, 202, 123, 121, 45, 40, 139, 152, 183, 77, 208, 21, 179, 171, 67, 20, 127, 133, 175, 203, 100, 107, 165, 128, 91, 85, 47, 42, 180, 136, 148, 115, 163, 102, 129, 31, 103, 134, 187, 4, 111, 87, 56, 13, 63, 72, 112, 182, 49, 178, 126, 69, 191, 162, 205, 76, 164, 19, 18, 188, 88, 141, 65, 106, 39, 157, 122, 79, 90, 143, 181, 135, 66, 5, 35, 167, 114, 154, 89, 110, 124, 96, 120, 37, 199, 185, 50, 142, 28, 48, 8, 101, 14, 86, 196, 184, 68, 145, 147, 117, 12, 55, 206, 189, 33, 61, 172, 204, 15, 29, 99, 9, 118, 26, 93, 46, 81, 109, 193, 23, 1, 166, 156, 34, 161, 2, 62, 16, 7, 105, 10, 70, 58, 168, 132, 53, 177, 144, 24, 130, 51, 153, 150, 44, 201, 209, 137, 195, 54, 82, 95, 17, 25, 155, 60, 176, 194, 192, 32, 27, 116, 98, 149, 198, 41, 190, 197, 84, 75, 92, 200, 151, 6, 104, 43, 159, 94, 119, 170, 207, 71, 22, 108, 83, 52, 146, 38, 160, 173, 113, 11, 186, 57, 140, 36, 125, 80, 131, 0]], Length: 211\n",
      "Robot Routes: [[[35, 167, 114, 154, 89, 110, 124, 96, 120, 37, 199, 185], [86, 196, 184, 68, 145, 147, 117, 12, 55, 206, 189, 33], [105, 10, 70, 58, 168, 132, 53, 177, 144, 24, 130, 51], [38, 160, 173, 113, 11, 186, 57, 140, 36, 125, 80, 131], [99, 9, 118, 26, 93, 46, 81, 109, 193, 23, 1, 166], [97, 73, 138, 78, 174, 3, 158, 74, 64, 202, 123, 121], [72, 112, 182, 49, 178, 126, 69, 191, 162, 205, 76, 164], [32, 27, 116, 98, 149, 198, 41, 190, 197, 84, 75, 92]]]\n",
      "Route: [0, 30, 59, 169, 97, 121, 45, 40, 139, 152, 183, 77, 208, 21, 179, 171, 67, 20, 127, 133, 175, 203, 100, 107, 165, 128, 91, 85, 47, 42, 180, 136, 148, 115, 163, 102, 129, 31, 103, 134, 187, 4, 111, 87, 56, 13, 63, 72, 164, 19, 18, 188, 88, 141, 65, 106, 39, 157, 122, 79, 90, 143, 181, 135, 66, 5, 35, 185, 50, 142, 28, 48, 8, 101, 14, 86, 33, 61, 172, 204, 15, 29, 99, 166, 156, 34, 161, 2, 62, 16, 7, 105, 51, 153, 150, 44, 201, 209, 137, 195, 54, 82, 95, 17, 25, 155, 60, 176, 194, 192, 32, 92, 200, 151, 6, 104, 43, 159, 94, 119, 170, 207, 71, 22, 108, 83, 52, 146, 38, 131, 0], Robot Group: [[35, 167, 114, 154, 89, 110, 124, 96, 120, 37, 199, 185], [86, 196, 184, 68, 145, 147, 117, 12, 55, 206, 189, 33], [105, 10, 70, 58, 168, 132, 53, 177, 144, 24, 130, 51], [38, 160, 173, 113, 11, 186, 57, 140, 36, 125, 80, 131], [99, 9, 118, 26, 93, 46, 81, 109, 193, 23, 1, 166], [97, 73, 138, 78, 174, 3, 158, 74, 64, 202, 123, 121], [72, 112, 182, 49, 178, 126, 69, 191, 162, 205, 76, 164], [32, 27, 116, 98, 149, 198, 41, 190, 197, 84, 75, 92]]\n",
      "Vehicle 0: 57151 m, 375.867 min, including 80.716 mins waiting time.\n",
      "Total distance of all routes: : 57151 m\n",
      "Maximum travel time: 375.867 min\n",
      "Trial 13...\n",
      "VRP\n",
      "Routes: [[0, 68, 51, 140, 62, 46, 110, 60, 16, 133, 48, 191, 175, 165, 81, 41, 174, 17, 187, 49, 178, 26, 65, 107, 206, 138, 77, 87, 170, 33, 126, 136, 115, 79, 143, 70, 3, 169, 31, 122, 10, 1, 179, 163, 35, 80, 194, 204, 200, 189, 120, 157, 69, 103, 205, 64, 18, 195, 36, 90, 102, 29, 11, 123, 145, 98, 93, 180, 83, 12, 56, 95, 53, 142, 105, 190, 71, 38, 154, 111, 13, 109, 24, 21, 5, 197, 72, 148, 134, 94, 75, 201, 159, 177, 158, 182, 160, 61, 85, 171, 9, 129, 131, 97, 30, 184, 161, 86, 32, 55, 106, 181, 15, 112, 199, 37, 164, 66, 91, 188, 208, 193, 63, 19, 209, 173, 52, 8, 147, 172, 151, 127, 100, 183, 192, 121, 176, 166, 45, 116, 82, 40, 6, 196, 203, 47, 114, 42, 128, 167, 59, 108, 44, 2, 198, 28, 78, 96, 137, 146, 162, 92, 20, 168, 144, 50, 4, 207, 101, 118, 141, 124, 153, 39, 135, 67, 152, 43, 156, 27, 89, 104, 74, 22, 23, 76, 132, 113, 119, 185, 73, 58, 117, 57, 88, 139, 14, 149, 99, 130, 202, 186, 84, 25, 34, 125, 155, 7, 150, 54, 0]], Length: 211\n",
      "Vehicle 0: 70511 m, 490.511 min, including 0 mins waiting time.\n",
      "Total distance of all routes: : 70511 m\n",
      "Maximum travel time: 490.511 min\n",
      "VRP-D\n",
      "Routes: [[0, 68, 51, 140, 62, 46, 110, 60, 16, 133, 48, 191, 175, 165, 81, 41, 174, 17, 187, 49, 178, 26, 65, 107, 206, 138, 77, 87, 170, 33, 126, 136, 115, 79, 143, 70, 3, 169, 31, 122, 10, 1, 179, 163, 35, 80, 194, 204, 200, 189, 120, 157, 69, 103, 205, 64, 18, 195, 36, 90, 102, 29, 11, 123, 145, 98, 93, 180, 83, 12, 56, 95, 53, 142, 105, 190, 71, 38, 154, 111, 13, 109, 24, 21, 5, 197, 72, 148, 134, 94, 75, 201, 159, 177, 158, 182, 160, 61, 85, 171, 9, 129, 131, 97, 30, 184, 161, 86, 32, 55, 106, 181, 15, 112, 199, 37, 164, 66, 91, 188, 208, 193, 63, 19, 209, 173, 52, 8, 147, 172, 151, 127, 100, 183, 192, 121, 176, 166, 45, 116, 82, 40, 6, 196, 203, 47, 114, 42, 128, 167, 59, 108, 44, 2, 198, 28, 78, 96, 137, 146, 162, 92, 20, 168, 144, 50, 4, 207, 101, 118, 141, 124, 153, 39, 135, 67, 152, 43, 156, 27, 89, 104, 74, 22, 23, 76, 132, 113, 119, 185, 73, 58, 117, 57, 88, 139, 14, 149, 99, 130, 202, 186, 84, 25, 34, 125, 155, 7, 150, 54, 0]], Length: 211\n",
      "Vehicle 0: 66059 m, 468.646 min, including 18.587 mins waiting time.\n",
      "Total distance of all routes: : 66059 m\n",
      "Maximum travel time: 468.646 min\n",
      "VRP-R\n",
      "Routes: [[0, 68, 51, 140, 62, 46, 110, 60, 16, 133, 48, 191, 175, 165, 81, 41, 174, 17, 187, 49, 178, 26, 65, 107, 206, 138, 77, 87, 170, 33, 126, 136, 115, 79, 143, 70, 3, 169, 31, 122, 10, 1, 179, 163, 35, 80, 194, 204, 200, 189, 120, 157, 69, 103, 205, 64, 18, 195, 36, 90, 102, 29, 11, 123, 145, 98, 93, 180, 83, 12, 56, 95, 53, 142, 105, 190, 71, 38, 154, 111, 13, 109, 24, 21, 5, 197, 72, 148, 134, 94, 75, 201, 159, 177, 158, 182, 160, 61, 85, 171, 9, 129, 131, 97, 30, 184, 161, 86, 32, 55, 106, 181, 15, 112, 199, 37, 164, 66, 91, 188, 208, 193, 63, 19, 209, 173, 52, 8, 147, 172, 151, 127, 100, 183, 192, 121, 176, 166, 45, 116, 82, 40, 6, 196, 203, 47, 114, 42, 128, 167, 59, 108, 44, 2, 198, 28, 78, 96, 137, 146, 162, 92, 20, 168, 144, 50, 4, 207, 101, 118, 141, 124, 153, 39, 135, 67, 152, 43, 156, 27, 89, 104, 74, 22, 23, 76, 132, 113, 119, 185, 73, 58, 117, 57, 88, 139, 14, 149, 99, 130, 202, 186, 84, 25, 34, 125, 155, 7, 150, 54, 0]], Length: 211\n",
      "Robot Routes: [[[180, 83, 12, 56, 95, 53, 142, 105, 190, 71, 38, 154], [52, 8, 147, 172, 151, 127, 100, 183, 192, 121, 176, 166], [152, 43, 156, 27, 89, 104, 74, 22, 23, 76, 132, 113], [65, 107, 206, 138, 77, 87, 170, 33, 126, 136, 115, 79], [111, 13, 109, 24, 21, 5, 197, 72, 148, 134, 94, 75], [116, 82, 40, 6, 196, 203, 47, 114, 42, 128, 167, 59], [137, 146, 162, 92, 20, 168, 144, 50, 4, 207, 101, 118]]]\n",
      "Route: [0, 68, 51, 140, 62, 46, 110, 60, 16, 133, 48, 191, 175, 165, 81, 41, 174, 17, 187, 49, 178, 26, 65, 79, 143, 70, 3, 169, 31, 122, 10, 1, 179, 163, 35, 80, 194, 204, 200, 189, 120, 157, 69, 103, 205, 64, 18, 195, 36, 90, 102, 29, 11, 123, 145, 98, 93, 180, 154, 111, 75, 201, 159, 177, 158, 182, 160, 61, 85, 171, 9, 129, 131, 97, 30, 184, 161, 86, 32, 55, 106, 181, 15, 112, 199, 37, 164, 66, 91, 188, 208, 193, 63, 19, 209, 173, 52, 166, 45, 116, 59, 108, 44, 2, 198, 28, 78, 96, 137, 118, 141, 124, 153, 39, 135, 67, 152, 113, 119, 185, 73, 58, 117, 57, 88, 139, 14, 149, 99, 130, 202, 186, 84, 25, 34, 125, 155, 7, 150, 54, 0], Robot Group: [[180, 83, 12, 56, 95, 53, 142, 105, 190, 71, 38, 154], [52, 8, 147, 172, 151, 127, 100, 183, 192, 121, 176, 166], [152, 43, 156, 27, 89, 104, 74, 22, 23, 76, 132, 113], [65, 107, 206, 138, 77, 87, 170, 33, 126, 136, 115, 79], [111, 13, 109, 24, 21, 5, 197, 72, 148, 134, 94, 75], [116, 82, 40, 6, 196, 203, 47, 114, 42, 128, 167, 59], [137, 146, 162, 92, 20, 168, 144, 50, 4, 207, 101, 118]]\n",
      "Vehicle 0: 62825 m, 359.737 min, including 16.912 mins waiting time.\n",
      "Total distance of all routes: : 62825 m\n",
      "Maximum travel time: 359.737 min\n",
      "VRP-RD\n",
      "Routes: [[0, 68, 51, 140, 62, 46, 110, 60, 16, 133, 48, 191, 175, 165, 81, 41, 174, 17, 187, 49, 178, 26, 65, 107, 206, 138, 77, 87, 170, 33, 126, 136, 115, 79, 143, 70, 3, 169, 31, 122, 10, 1, 179, 163, 35, 80, 194, 204, 200, 189, 120, 157, 69, 103, 205, 64, 18, 195, 36, 90, 102, 29, 11, 123, 145, 98, 93, 180, 83, 12, 56, 95, 53, 142, 105, 190, 71, 38, 154, 111, 13, 109, 24, 21, 5, 197, 72, 148, 134, 94, 75, 201, 159, 177, 158, 182, 160, 61, 85, 171, 9, 129, 131, 97, 30, 184, 161, 86, 32, 55, 106, 181, 15, 112, 199, 37, 164, 66, 91, 188, 208, 193, 63, 19, 209, 173, 52, 8, 147, 172, 151, 127, 100, 183, 192, 121, 176, 166, 45, 116, 82, 40, 6, 196, 203, 47, 114, 42, 128, 167, 59, 108, 44, 2, 198, 28, 78, 96, 137, 146, 162, 92, 20, 168, 144, 50, 4, 207, 101, 118, 141, 124, 153, 39, 135, 67, 152, 43, 156, 27, 89, 104, 74, 22, 23, 76, 132, 113, 119, 185, 73, 58, 117, 57, 88, 139, 14, 149, 99, 130, 202, 186, 84, 25, 34, 125, 155, 7, 150, 54, 0]], Length: 211\n",
      "Robot Routes: [[[180, 83, 12, 56, 95, 53, 142, 105, 190, 71, 38, 154], [52, 8, 147, 172, 151, 127, 100, 183, 192, 121, 176, 166], [152, 43, 156, 27, 89, 104, 74, 22, 23, 76, 132, 113], [65, 107, 206, 138, 77, 87, 170, 33, 126, 136, 115, 79], [111, 13, 109, 24, 21, 5, 197, 72, 148, 134, 94, 75], [116, 82, 40, 6, 196, 203, 47, 114, 42, 128, 167, 59], [137, 146, 162, 92, 20, 168, 144, 50, 4, 207, 101, 118]]]\n",
      "Route: [0, 68, 51, 140, 62, 46, 110, 60, 16, 133, 48, 191, 175, 165, 81, 41, 174, 17, 187, 49, 178, 26, 65, 79, 143, 70, 3, 169, 31, 122, 10, 1, 179, 163, 35, 80, 194, 204, 200, 189, 120, 157, 69, 103, 205, 64, 18, 195, 36, 90, 102, 29, 11, 123, 145, 98, 93, 180, 154, 111, 75, 201, 159, 177, 158, 182, 160, 61, 85, 171, 9, 129, 131, 97, 30, 184, 161, 86, 32, 55, 106, 181, 15, 112, 199, 37, 164, 66, 91, 188, 208, 193, 63, 19, 209, 173, 52, 166, 45, 116, 59, 108, 44, 2, 198, 28, 78, 96, 137, 118, 141, 124, 153, 39, 135, 67, 152, 113, 119, 185, 73, 58, 117, 57, 88, 139, 14, 149, 99, 130, 202, 186, 84, 25, 34, 125, 155, 7, 150, 54, 0], Robot Group: [[180, 83, 12, 56, 95, 53, 142, 105, 190, 71, 38, 154], [52, 8, 147, 172, 151, 127, 100, 183, 192, 121, 176, 166], [152, 43, 156, 27, 89, 104, 74, 22, 23, 76, 132, 113], [65, 107, 206, 138, 77, 87, 170, 33, 126, 136, 115, 79], [111, 13, 109, 24, 21, 5, 197, 72, 148, 134, 94, 75], [116, 82, 40, 6, 196, 203, 47, 114, 42, 128, 167, 59], [137, 146, 162, 92, 20, 168, 144, 50, 4, 207, 101, 118]]\n",
      "Vehicle 0: 59747 m, 349.632 min, including 33.885 mins waiting time.\n",
      "Total distance of all routes: : 59747 m\n",
      "Maximum travel time: 349.632 min\n",
      "Trial 14...\n",
      "VRP\n",
      "Routes: [[0, 22, 198, 89, 19, 178, 140, 181, 79, 172, 139, 180, 112, 126, 189, 43, 28, 12, 21, 104, 132, 207, 74, 134, 94, 64, 186, 203, 72, 56, 117, 171, 162, 14, 29, 31, 98, 115, 35, 58, 76, 9, 182, 23, 111, 1, 81, 202, 18, 200, 142, 87, 168, 185, 159, 116, 147, 129, 101, 188, 169, 45, 193, 15, 156, 144, 157, 209, 49, 175, 138, 166, 92, 160, 40, 37, 95, 113, 73, 25, 106, 38, 50, 183, 201, 110, 161, 39, 53, 158, 13, 47, 44, 195, 127, 71, 33, 84, 68, 36, 46, 34, 2, 208, 108, 133, 17, 120, 123, 154, 93, 119, 75, 109, 199, 67, 6, 3, 137, 62, 4, 196, 107, 78, 83, 61, 86, 82, 102, 70, 65, 42, 41, 10, 151, 194, 191, 184, 153, 145, 88, 155, 91, 114, 173, 118, 63, 60, 205, 11, 135, 174, 26, 177, 30, 77, 100, 167, 24, 69, 99, 51, 27, 121, 143, 122, 48, 32, 130, 5, 66, 20, 165, 176, 192, 197, 8, 59, 204, 170, 55, 128, 57, 52, 125, 190, 146, 149, 90, 54, 7, 96, 187, 16, 148, 103, 179, 152, 105, 163, 124, 206, 136, 131, 85, 141, 164, 80, 97, 150, 0]], Length: 211\n",
      "Vehicle 0: 69328 m, 489.328 min, including 0 mins waiting time.\n",
      "Total distance of all routes: : 69328 m\n",
      "Maximum travel time: 489.328 min\n",
      "VRP-D\n",
      "Routes: [[0, 22, 198, 89, 19, 178, 140, 181, 79, 172, 139, 180, 112, 126, 189, 43, 28, 12, 21, 104, 132, 207, 74, 134, 94, 64, 186, 203, 72, 56, 117, 171, 162, 14, 29, 31, 98, 115, 35, 58, 76, 9, 182, 23, 111, 1, 81, 202, 18, 200, 142, 87, 168, 185, 159, 116, 147, 129, 101, 188, 169, 45, 193, 15, 156, 144, 157, 209, 49, 175, 138, 166, 92, 160, 40, 37, 95, 113, 73, 25, 106, 38, 50, 183, 201, 110, 161, 39, 53, 158, 13, 47, 44, 195, 127, 71, 33, 84, 68, 36, 46, 34, 2, 208, 108, 133, 17, 120, 123, 154, 93, 119, 75, 109, 199, 67, 6, 3, 137, 62, 4, 196, 107, 78, 83, 61, 86, 82, 102, 70, 65, 42, 41, 10, 151, 194, 191, 184, 153, 145, 88, 155, 91, 114, 173, 118, 63, 60, 205, 11, 135, 174, 26, 177, 30, 77, 100, 167, 24, 69, 99, 51, 27, 121, 143, 122, 48, 32, 130, 5, 66, 20, 165, 176, 192, 197, 8, 59, 204, 170, 55, 128, 57, 52, 125, 190, 146, 149, 90, 54, 7, 96, 187, 16, 148, 103, 179, 152, 105, 163, 124, 206, 136, 131, 85, 141, 164, 80, 97, 150, 0]], Length: 211\n",
      "Vehicle 0: 67105 m, 467.497 min, including 12.392 mins waiting time.\n",
      "Total distance of all routes: : 67105 m\n",
      "Maximum travel time: 467.497 min\n",
      "VRP-R\n",
      "Routes: [[0, 22, 198, 89, 19, 178, 140, 181, 79, 172, 139, 180, 112, 126, 189, 43, 28, 12, 21, 104, 132, 207, 74, 134, 94, 64, 186, 203, 72, 56, 117, 171, 162, 14, 29, 31, 98, 115, 35, 58, 76, 9, 182, 23, 111, 1, 81, 202, 18, 200, 142, 87, 168, 185, 159, 116, 147, 129, 101, 188, 169, 45, 193, 15, 156, 144, 157, 209, 49, 175, 138, 166, 92, 160, 40, 37, 95, 113, 73, 25, 106, 38, 50, 183, 201, 110, 161, 39, 53, 158, 13, 47, 44, 195, 127, 71, 33, 84, 68, 36, 46, 34, 2, 208, 108, 133, 17, 120, 123, 154, 93, 119, 75, 109, 199, 67, 6, 3, 137, 62, 4, 196, 107, 78, 83, 61, 86, 82, 102, 70, 65, 42, 41, 10, 151, 194, 191, 184, 153, 145, 88, 155, 91, 114, 173, 118, 63, 60, 205, 11, 135, 174, 26, 177, 30, 77, 100, 167, 24, 69, 99, 51, 27, 121, 143, 122, 48, 32, 130, 5, 66, 20, 165, 176, 192, 197, 8, 59, 204, 170, 55, 128, 57, 52, 125, 190, 146, 149, 90, 54, 7, 96, 187, 16, 148, 103, 179, 152, 105, 163, 124, 206, 136, 131, 85, 141, 164, 80, 97, 150, 0]], Length: 211\n",
      "Robot Routes: [[[75, 109, 199, 67, 6, 3, 137, 62, 4, 196, 107, 78], [185, 159, 116, 147, 129, 101, 188, 169, 45, 193, 15, 156], [139, 180, 112, 126, 189, 43, 28, 12, 21, 104, 132, 207], [191, 184, 153, 145, 88, 155, 91, 114, 173, 118, 63, 60], [157, 209, 49, 175, 138, 166, 92, 160, 40, 37, 95, 113], [103, 179, 152, 105, 163, 124, 206, 136, 131, 85, 141, 164], [26, 177, 30, 77, 100, 167, 24, 69, 99, 51, 27, 121], [71, 33, 84, 68, 36, 46, 34, 2, 208, 108, 133, 17]]]\n",
      "Route: [0, 22, 198, 89, 19, 178, 140, 181, 79, 172, 139, 207, 74, 134, 94, 64, 186, 203, 72, 56, 117, 171, 162, 14, 29, 31, 98, 115, 35, 58, 76, 9, 182, 23, 111, 1, 81, 202, 18, 200, 142, 87, 168, 185, 156, 144, 157, 113, 73, 25, 106, 38, 50, 183, 201, 110, 161, 39, 53, 158, 13, 47, 44, 195, 127, 71, 17, 120, 123, 154, 93, 119, 75, 78, 83, 61, 86, 82, 102, 70, 65, 42, 41, 10, 151, 194, 191, 60, 205, 11, 135, 174, 26, 121, 143, 122, 48, 32, 130, 5, 66, 20, 165, 176, 192, 197, 8, 59, 204, 170, 55, 128, 57, 52, 125, 190, 146, 149, 90, 54, 7, 96, 187, 16, 148, 103, 164, 80, 97, 150, 0], Robot Group: [[75, 109, 199, 67, 6, 3, 137, 62, 4, 196, 107, 78], [185, 159, 116, 147, 129, 101, 188, 169, 45, 193, 15, 156], [139, 180, 112, 126, 189, 43, 28, 12, 21, 104, 132, 207], [191, 184, 153, 145, 88, 155, 91, 114, 173, 118, 63, 60], [157, 209, 49, 175, 138, 166, 92, 160, 40, 37, 95, 113], [103, 179, 152, 105, 163, 124, 206, 136, 131, 85, 141, 164], [26, 177, 30, 77, 100, 167, 24, 69, 99, 51, 27, 121], [71, 33, 84, 68, 36, 46, 34, 2, 208, 108, 133, 17]]\n",
      "Vehicle 0: 59356 m, 353.768 min, including 34.412 mins waiting time.\n",
      "Total distance of all routes: : 59356 m\n",
      "Maximum travel time: 353.768 min\n",
      "VRP-RD\n",
      "Routes: [[0, 22, 198, 89, 19, 178, 140, 181, 79, 172, 139, 180, 112, 126, 189, 43, 28, 12, 21, 104, 132, 207, 74, 134, 94, 64, 186, 203, 72, 56, 117, 171, 162, 14, 29, 31, 98, 115, 35, 58, 76, 9, 182, 23, 111, 1, 81, 202, 18, 200, 142, 87, 168, 185, 159, 116, 147, 129, 101, 188, 169, 45, 193, 15, 156, 144, 157, 209, 49, 175, 138, 166, 92, 160, 40, 37, 95, 113, 73, 25, 106, 38, 50, 183, 201, 110, 161, 39, 53, 158, 13, 47, 44, 195, 127, 71, 33, 84, 68, 36, 46, 34, 2, 208, 108, 133, 17, 120, 123, 154, 93, 119, 75, 109, 199, 67, 6, 3, 137, 62, 4, 196, 107, 78, 83, 61, 86, 82, 102, 70, 65, 42, 41, 10, 151, 194, 191, 184, 153, 145, 88, 155, 91, 114, 173, 118, 63, 60, 205, 11, 135, 174, 26, 177, 30, 77, 100, 167, 24, 69, 99, 51, 27, 121, 143, 122, 48, 32, 130, 5, 66, 20, 165, 176, 192, 197, 8, 59, 204, 170, 55, 128, 57, 52, 125, 190, 146, 149, 90, 54, 7, 96, 187, 16, 148, 103, 179, 152, 105, 163, 124, 206, 136, 131, 85, 141, 164, 80, 97, 150, 0]], Length: 211\n",
      "Robot Routes: [[[75, 109, 199, 67, 6, 3, 137, 62, 4, 196, 107, 78], [185, 159, 116, 147, 129, 101, 188, 169, 45, 193, 15, 156], [139, 180, 112, 126, 189, 43, 28, 12, 21, 104, 132, 207], [191, 184, 153, 145, 88, 155, 91, 114, 173, 118, 63, 60], [157, 209, 49, 175, 138, 166, 92, 160, 40, 37, 95, 113], [103, 179, 152, 105, 163, 124, 206, 136, 131, 85, 141, 164], [26, 177, 30, 77, 100, 167, 24, 69, 99, 51, 27, 121], [71, 33, 84, 68, 36, 46, 34, 2, 208, 108, 133, 17]]]\n",
      "Route: [0, 22, 198, 89, 19, 178, 140, 181, 79, 172, 139, 207, 74, 134, 94, 64, 186, 203, 72, 56, 117, 171, 162, 14, 29, 31, 98, 115, 35, 58, 76, 9, 182, 23, 111, 1, 81, 202, 18, 200, 142, 87, 168, 185, 156, 144, 157, 113, 73, 25, 106, 38, 50, 183, 201, 110, 161, 39, 53, 158, 13, 47, 44, 195, 127, 71, 17, 120, 123, 154, 93, 119, 75, 78, 83, 61, 86, 82, 102, 70, 65, 42, 41, 10, 151, 194, 191, 60, 205, 11, 135, 174, 26, 121, 143, 122, 48, 32, 130, 5, 66, 20, 165, 176, 192, 197, 8, 59, 204, 170, 55, 128, 57, 52, 125, 190, 146, 149, 90, 54, 7, 96, 187, 16, 148, 103, 164, 80, 97, 150, 0], Robot Group: [[75, 109, 199, 67, 6, 3, 137, 62, 4, 196, 107, 78], [185, 159, 116, 147, 129, 101, 188, 169, 45, 193, 15, 156], [139, 180, 112, 126, 189, 43, 28, 12, 21, 104, 132, 207], [191, 184, 153, 145, 88, 155, 91, 114, 173, 118, 63, 60], [157, 209, 49, 175, 138, 166, 92, 160, 40, 37, 95, 113], [103, 179, 152, 105, 163, 124, 206, 136, 131, 85, 141, 164], [26, 177, 30, 77, 100, 167, 24, 69, 99, 51, 27, 121], [71, 33, 84, 68, 36, 46, 34, 2, 208, 108, 133, 17]]\n",
      "Vehicle 0: 56842 m, 342.188 min, including 45.346 mins waiting time.\n",
      "Total distance of all routes: : 56842 m\n",
      "Maximum travel time: 342.188 min\n",
      "Trial 15...\n",
      "VRP\n",
      "Routes: [[0, 154, 180, 117, 83, 81, 147, 145, 95, 8, 148, 177, 91, 79, 107, 38, 51, 134, 199, 189, 122, 102, 42, 151, 32, 152, 186, 26, 49, 67, 97, 155, 69, 29, 16, 179, 165, 43, 31, 187, 27, 108, 141, 103, 98, 128, 47, 41, 115, 112, 82, 2, 202, 111, 138, 60, 39, 143, 190, 182, 109, 33, 208, 65, 62, 105, 50, 137, 52, 71, 64, 185, 19, 113, 184, 28, 183, 73, 63, 25, 181, 72, 196, 45, 100, 131, 127, 53, 198, 197, 90, 124, 200, 75, 30, 153, 140, 207, 132, 104, 168, 136, 94, 188, 163, 194, 158, 192, 5, 114, 205, 84, 119, 21, 204, 55, 66, 80, 123, 176, 193, 160, 118, 89, 93, 203, 135, 88, 116, 58, 167, 106, 101, 121, 146, 24, 48, 15, 173, 54, 37, 23, 14, 17, 164, 156, 133, 40, 171, 110, 22, 129, 77, 126, 1, 159, 36, 56, 125, 6, 76, 142, 149, 166, 99, 12, 68, 18, 9, 57, 85, 10, 70, 7, 150, 86, 35, 157, 74, 169, 13, 46, 209, 206, 178, 3, 201, 172, 59, 162, 139, 92, 4, 11, 96, 61, 78, 34, 174, 87, 175, 161, 191, 130, 44, 195, 120, 144, 170, 20, 0]], Length: 211\n",
      "Vehicle 0: 72856 m, 492.856 min, including 0 mins waiting time.\n",
      "Total distance of all routes: : 72856 m\n",
      "Maximum travel time: 492.856 min\n",
      "VRP-D\n",
      "Routes: [[0, 154, 180, 117, 83, 81, 147, 145, 95, 8, 148, 177, 91, 79, 107, 38, 51, 134, 199, 189, 122, 102, 42, 151, 32, 152, 186, 26, 49, 67, 97, 155, 69, 29, 16, 179, 165, 43, 31, 187, 27, 108, 141, 103, 98, 128, 47, 41, 115, 112, 82, 2, 202, 111, 138, 60, 39, 143, 190, 182, 109, 33, 208, 65, 62, 105, 50, 137, 52, 71, 64, 185, 19, 113, 184, 28, 183, 73, 63, 25, 181, 72, 196, 45, 100, 131, 127, 53, 198, 197, 90, 124, 200, 75, 30, 153, 140, 207, 132, 104, 168, 136, 94, 188, 163, 194, 158, 192, 5, 114, 205, 84, 119, 21, 204, 55, 66, 80, 123, 176, 193, 160, 118, 89, 93, 203, 135, 88, 116, 58, 167, 106, 101, 121, 146, 24, 48, 15, 173, 54, 37, 23, 14, 17, 164, 156, 133, 40, 171, 110, 22, 129, 77, 126, 1, 159, 36, 56, 125, 6, 76, 142, 149, 166, 99, 12, 68, 18, 9, 57, 85, 10, 70, 7, 150, 86, 35, 157, 74, 169, 13, 46, 209, 206, 178, 3, 201, 172, 59, 162, 139, 92, 4, 11, 96, 61, 78, 34, 174, 87, 175, 161, 191, 130, 44, 195, 120, 144, 170, 20, 0]], Length: 211\n",
      "Vehicle 0: 68150 m, 469.243 min, including 15.093 mins waiting time.\n",
      "Total distance of all routes: : 68150 m\n",
      "Maximum travel time: 469.243 min\n",
      "VRP-R\n",
      "Routes: [[0, 154, 180, 117, 83, 81, 147, 145, 95, 8, 148, 177, 91, 79, 107, 38, 51, 134, 199, 189, 122, 102, 42, 151, 32, 152, 186, 26, 49, 67, 97, 155, 69, 29, 16, 179, 165, 43, 31, 187, 27, 108, 141, 103, 98, 128, 47, 41, 115, 112, 82, 2, 202, 111, 138, 60, 39, 143, 190, 182, 109, 33, 208, 65, 62, 105, 50, 137, 52, 71, 64, 185, 19, 113, 184, 28, 183, 73, 63, 25, 181, 72, 196, 45, 100, 131, 127, 53, 198, 197, 90, 124, 200, 75, 30, 153, 140, 207, 132, 104, 168, 136, 94, 188, 163, 194, 158, 192, 5, 114, 205, 84, 119, 21, 204, 55, 66, 80, 123, 176, 193, 160, 118, 89, 93, 203, 135, 88, 116, 58, 167, 106, 101, 121, 146, 24, 48, 15, 173, 54, 37, 23, 14, 17, 164, 156, 133, 40, 171, 110, 22, 129, 77, 126, 1, 159, 36, 56, 125, 6, 76, 142, 149, 166, 99, 12, 68, 18, 9, 57, 85, 10, 70, 7, 150, 86, 35, 157, 74, 169, 13, 46, 209, 206, 178, 3, 201, 172, 59, 162, 139, 92, 4, 11, 96, 61, 78, 34, 174, 87, 175, 161, 191, 130, 44, 195, 120, 144, 170, 20, 0]], Length: 211\n",
      "Robot Routes: [[[47, 41, 115, 112, 82, 2, 202, 111, 138, 60, 39, 143], [200, 75, 30, 153, 140, 207, 132, 104, 168, 136, 94, 188], [95, 8, 148, 177, 91, 79, 107, 38, 51, 134, 199, 189], [206, 178, 3, 201, 172, 59, 162, 139, 92, 4, 11, 96], [29, 16, 179, 165, 43, 31, 187, 27, 108, 141, 103, 98], [89, 93, 203, 135, 88, 116, 58, 167, 106, 101, 121, 146], [122, 102, 42, 151, 32, 152, 186, 26, 49, 67, 97, 155]]]\n",
      "Route: [0, 154, 180, 117, 83, 81, 147, 145, 95, 189, 122, 155, 69, 29, 98, 128, 47, 143, 190, 182, 109, 33, 208, 65, 62, 105, 50, 137, 52, 71, 64, 185, 19, 113, 184, 28, 183, 73, 63, 25, 181, 72, 196, 45, 100, 131, 127, 53, 198, 197, 90, 124, 200, 188, 163, 194, 158, 192, 5, 114, 205, 84, 119, 21, 204, 55, 66, 80, 123, 176, 193, 160, 118, 89, 146, 24, 48, 15, 173, 54, 37, 23, 14, 17, 164, 156, 133, 40, 171, 110, 22, 129, 77, 126, 1, 159, 36, 56, 125, 6, 76, 142, 149, 166, 99, 12, 68, 18, 9, 57, 85, 10, 70, 7, 150, 86, 35, 157, 74, 169, 13, 46, 209, 206, 96, 61, 78, 34, 174, 87, 175, 161, 191, 130, 44, 195, 120, 144, 170, 20, 0], Robot Group: [[47, 41, 115, 112, 82, 2, 202, 111, 138, 60, 39, 143], [200, 75, 30, 153, 140, 207, 132, 104, 168, 136, 94, 188], [95, 8, 148, 177, 91, 79, 107, 38, 51, 134, 199, 189], [206, 178, 3, 201, 172, 59, 162, 139, 92, 4, 11, 96], [29, 16, 179, 165, 43, 31, 187, 27, 108, 141, 103, 98], [89, 93, 203, 135, 88, 116, 58, 167, 106, 101, 121, 146], [122, 102, 42, 151, 32, 152, 186, 26, 49, 67, 97, 155]]\n",
      "Vehicle 0: 65381 m, 398.939 min, including 53.558 mins waiting time.\n",
      "Total distance of all routes: : 65381 m\n",
      "Maximum travel time: 398.939 min\n",
      "VRP-RD\n",
      "Routes: [[0, 154, 180, 117, 83, 81, 147, 145, 95, 8, 148, 177, 91, 79, 107, 38, 51, 134, 199, 189, 122, 102, 42, 151, 32, 152, 186, 26, 49, 67, 97, 155, 69, 29, 16, 179, 165, 43, 31, 187, 27, 108, 141, 103, 98, 128, 47, 41, 115, 112, 82, 2, 202, 111, 138, 60, 39, 143, 190, 182, 109, 33, 208, 65, 62, 105, 50, 137, 52, 71, 64, 185, 19, 113, 184, 28, 183, 73, 63, 25, 181, 72, 196, 45, 100, 131, 127, 53, 198, 197, 90, 124, 200, 75, 30, 153, 140, 207, 132, 104, 168, 136, 94, 188, 163, 194, 158, 192, 5, 114, 205, 84, 119, 21, 204, 55, 66, 80, 123, 176, 193, 160, 118, 89, 93, 203, 135, 88, 116, 58, 167, 106, 101, 121, 146, 24, 48, 15, 173, 54, 37, 23, 14, 17, 164, 156, 133, 40, 171, 110, 22, 129, 77, 126, 1, 159, 36, 56, 125, 6, 76, 142, 149, 166, 99, 12, 68, 18, 9, 57, 85, 10, 70, 7, 150, 86, 35, 157, 74, 169, 13, 46, 209, 206, 178, 3, 201, 172, 59, 162, 139, 92, 4, 11, 96, 61, 78, 34, 174, 87, 175, 161, 191, 130, 44, 195, 120, 144, 170, 20, 0]], Length: 211\n",
      "Robot Routes: [[[47, 41, 115, 112, 82, 2, 202, 111, 138, 60, 39, 143], [200, 75, 30, 153, 140, 207, 132, 104, 168, 136, 94, 188], [95, 8, 148, 177, 91, 79, 107, 38, 51, 134, 199, 189], [206, 178, 3, 201, 172, 59, 162, 139, 92, 4, 11, 96], [29, 16, 179, 165, 43, 31, 187, 27, 108, 141, 103, 98], [89, 93, 203, 135, 88, 116, 58, 167, 106, 101, 121, 146], [122, 102, 42, 151, 32, 152, 186, 26, 49, 67, 97, 155]]]\n",
      "Route: [0, 154, 180, 117, 83, 81, 147, 145, 95, 189, 122, 155, 69, 29, 98, 128, 47, 143, 190, 182, 109, 33, 208, 65, 62, 105, 50, 137, 52, 71, 64, 185, 19, 113, 184, 28, 183, 73, 63, 25, 181, 72, 196, 45, 100, 131, 127, 53, 198, 197, 90, 124, 200, 188, 163, 194, 158, 192, 5, 114, 205, 84, 119, 21, 204, 55, 66, 80, 123, 176, 193, 160, 118, 89, 146, 24, 48, 15, 173, 54, 37, 23, 14, 17, 164, 156, 133, 40, 171, 110, 22, 129, 77, 126, 1, 159, 36, 56, 125, 6, 76, 142, 149, 166, 99, 12, 68, 18, 9, 57, 85, 10, 70, 7, 150, 86, 35, 157, 74, 169, 13, 46, 209, 206, 96, 61, 78, 34, 174, 87, 175, 161, 191, 130, 44, 195, 120, 144, 170, 20, 0], Robot Group: [[47, 41, 115, 112, 82, 2, 202, 111, 138, 60, 39, 143], [200, 75, 30, 153, 140, 207, 132, 104, 168, 136, 94, 188], [95, 8, 148, 177, 91, 79, 107, 38, 51, 134, 199, 189], [206, 178, 3, 201, 172, 59, 162, 139, 92, 4, 11, 96], [29, 16, 179, 165, 43, 31, 187, 27, 108, 141, 103, 98], [89, 93, 203, 135, 88, 116, 58, 167, 106, 101, 121, 146], [122, 102, 42, 151, 32, 152, 186, 26, 49, 67, 97, 155]]\n",
      "Vehicle 0: 62710 m, 388.346 min, including 69.636 mins waiting time.\n",
      "Total distance of all routes: : 62710 m\n",
      "Maximum travel time: 388.346 min\n",
      "Trial 16...\n",
      "VRP\n",
      "Routes: [[0, 85, 81, 113, 170, 4, 62, 94, 130, 37, 40, 141, 119, 101, 79, 204, 178, 108, 58, 49, 149, 208, 197, 203, 6, 56, 164, 206, 171, 89, 122, 66, 63, 29, 46, 185, 133, 180, 65, 47, 126, 145, 176, 165, 105, 95, 159, 27, 143, 60, 61, 67, 92, 26, 136, 25, 189, 71, 146, 123, 22, 83, 156, 11, 161, 2, 33, 191, 188, 86, 68, 158, 139, 45, 76, 57, 9, 177, 20, 116, 194, 179, 200, 87, 18, 13, 10, 169, 19, 96, 195, 36, 115, 1, 44, 142, 16, 187, 75, 120, 167, 137, 147, 181, 190, 148, 15, 111, 107, 50, 52, 202, 166, 98, 53, 90, 192, 205, 12, 207, 114, 21, 144, 132, 127, 186, 91, 97, 173, 17, 78, 109, 110, 106, 74, 134, 51, 3, 201, 41, 175, 42, 124, 151, 8, 28, 69, 150, 154, 30, 43, 152, 48, 140, 135, 184, 153, 129, 77, 104, 99, 70, 128, 183, 117, 32, 5, 160, 138, 163, 155, 193, 14, 131, 38, 64, 112, 157, 172, 82, 162, 39, 55, 35, 118, 174, 72, 59, 100, 34, 209, 182, 31, 23, 121, 125, 196, 168, 54, 198, 7, 84, 24, 199, 80, 73, 88, 103, 93, 102, 0]], Length: 211\n",
      "Vehicle 0: 74165 m, 494.165 min, including 0 mins waiting time.\n",
      "Total distance of all routes: : 74165 m\n",
      "Maximum travel time: 494.165 min\n",
      "VRP-D\n",
      "Routes: [[0, 85, 81, 113, 170, 4, 62, 94, 130, 37, 40, 141, 119, 101, 79, 204, 178, 108, 58, 49, 149, 208, 197, 203, 6, 56, 164, 206, 171, 89, 122, 66, 63, 29, 46, 185, 133, 180, 65, 47, 126, 145, 176, 165, 105, 95, 159, 27, 143, 60, 61, 67, 92, 26, 136, 25, 189, 71, 146, 123, 22, 83, 156, 11, 161, 2, 33, 191, 188, 86, 68, 158, 139, 45, 76, 57, 9, 177, 20, 116, 194, 179, 200, 87, 18, 13, 10, 169, 19, 96, 195, 36, 115, 1, 44, 142, 16, 187, 75, 120, 167, 137, 147, 181, 190, 148, 15, 111, 107, 50, 52, 202, 166, 98, 53, 90, 192, 205, 12, 207, 114, 21, 144, 132, 127, 186, 91, 97, 173, 17, 78, 109, 110, 106, 74, 134, 51, 3, 201, 41, 175, 42, 124, 151, 8, 28, 69, 150, 154, 30, 43, 152, 48, 140, 135, 184, 153, 129, 77, 104, 99, 70, 128, 183, 117, 32, 5, 160, 138, 163, 155, 193, 14, 131, 38, 64, 112, 157, 172, 82, 162, 39, 55, 35, 118, 174, 72, 59, 100, 34, 209, 182, 31, 23, 121, 125, 196, 168, 54, 198, 7, 84, 24, 199, 80, 73, 88, 103, 93, 102, 0]], Length: 211\n",
      "Vehicle 0: 71317 m, 469.681 min, including 12.364 mins waiting time.\n",
      "Total distance of all routes: : 71317 m\n",
      "Maximum travel time: 469.681 min\n",
      "VRP-R\n",
      "Routes: [[0, 85, 81, 113, 170, 4, 62, 94, 130, 37, 40, 141, 119, 101, 79, 204, 178, 108, 58, 49, 149, 208, 197, 203, 6, 56, 164, 206, 171, 89, 122, 66, 63, 29, 46, 185, 133, 180, 65, 47, 126, 145, 176, 165, 105, 95, 159, 27, 143, 60, 61, 67, 92, 26, 136, 25, 189, 71, 146, 123, 22, 83, 156, 11, 161, 2, 33, 191, 188, 86, 68, 158, 139, 45, 76, 57, 9, 177, 20, 116, 194, 179, 200, 87, 18, 13, 10, 169, 19, 96, 195, 36, 115, 1, 44, 142, 16, 187, 75, 120, 167, 137, 147, 181, 190, 148, 15, 111, 107, 50, 52, 202, 166, 98, 53, 90, 192, 205, 12, 207, 114, 21, 144, 132, 127, 186, 91, 97, 173, 17, 78, 109, 110, 106, 74, 134, 51, 3, 201, 41, 175, 42, 124, 151, 8, 28, 69, 150, 154, 30, 43, 152, 48, 140, 135, 184, 153, 129, 77, 104, 99, 70, 128, 183, 117, 32, 5, 160, 138, 163, 155, 193, 14, 131, 38, 64, 112, 157, 172, 82, 162, 39, 55, 35, 118, 174, 72, 59, 100, 34, 209, 182, 31, 23, 121, 125, 196, 168, 54, 198, 7, 84, 24, 199, 80, 73, 88, 103, 93, 102, 0]], Length: 211\n",
      "Robot Routes: [[[147, 181, 190, 148, 15, 111, 107, 50, 52, 202, 166, 98], [30, 43, 152, 48, 140, 135, 184, 153, 129, 77, 104, 99], [139, 45, 76, 57, 9, 177, 20, 116, 194, 179, 200, 87], [160, 138, 163, 155, 193, 14, 131, 38, 64, 112, 157, 172], [185, 133, 180, 65, 47, 126, 145, 176, 165, 105, 95, 159], [27, 143, 60, 61, 67, 92, 26, 136, 25, 189, 71, 146], [106, 74, 134, 51, 3, 201, 41, 175, 42, 124, 151, 8]]]\n",
      "Route: [0, 85, 81, 113, 170, 4, 62, 94, 130, 37, 40, 141, 119, 101, 79, 204, 178, 108, 58, 49, 149, 208, 197, 203, 6, 56, 164, 206, 171, 89, 122, 66, 63, 29, 46, 185, 159, 27, 146, 123, 22, 83, 156, 11, 161, 2, 33, 191, 188, 86, 68, 158, 139, 87, 18, 13, 10, 169, 19, 96, 195, 36, 115, 1, 44, 142, 16, 187, 75, 120, 167, 137, 147, 98, 53, 90, 192, 205, 12, 207, 114, 21, 144, 132, 127, 186, 91, 97, 173, 17, 78, 109, 110, 106, 8, 28, 69, 150, 154, 30, 99, 70, 128, 183, 117, 32, 5, 160, 172, 82, 162, 39, 55, 35, 118, 174, 72, 59, 100, 34, 209, 182, 31, 23, 121, 125, 196, 168, 54, 198, 7, 84, 24, 199, 80, 73, 88, 103, 93, 102, 0], Robot Group: [[147, 181, 190, 148, 15, 111, 107, 50, 52, 202, 166, 98], [30, 43, 152, 48, 140, 135, 184, 153, 129, 77, 104, 99], [139, 45, 76, 57, 9, 177, 20, 116, 194, 179, 200, 87], [160, 138, 163, 155, 193, 14, 131, 38, 64, 112, 157, 172], [185, 133, 180, 65, 47, 126, 145, 176, 165, 105, 95, 159], [27, 143, 60, 61, 67, 92, 26, 136, 25, 189, 71, 146], [106, 74, 134, 51, 3, 201, 41, 175, 42, 124, 151, 8]]\n",
      "Vehicle 0: 61313 m, 362.451 min, including 21.138 mins waiting time.\n",
      "Total distance of all routes: : 61313 m\n",
      "Maximum travel time: 362.451 min\n",
      "VRP-RD\n",
      "Routes: [[0, 85, 81, 113, 170, 4, 62, 94, 130, 37, 40, 141, 119, 101, 79, 204, 178, 108, 58, 49, 149, 208, 197, 203, 6, 56, 164, 206, 171, 89, 122, 66, 63, 29, 46, 185, 133, 180, 65, 47, 126, 145, 176, 165, 105, 95, 159, 27, 143, 60, 61, 67, 92, 26, 136, 25, 189, 71, 146, 123, 22, 83, 156, 11, 161, 2, 33, 191, 188, 86, 68, 158, 139, 45, 76, 57, 9, 177, 20, 116, 194, 179, 200, 87, 18, 13, 10, 169, 19, 96, 195, 36, 115, 1, 44, 142, 16, 187, 75, 120, 167, 137, 147, 181, 190, 148, 15, 111, 107, 50, 52, 202, 166, 98, 53, 90, 192, 205, 12, 207, 114, 21, 144, 132, 127, 186, 91, 97, 173, 17, 78, 109, 110, 106, 74, 134, 51, 3, 201, 41, 175, 42, 124, 151, 8, 28, 69, 150, 154, 30, 43, 152, 48, 140, 135, 184, 153, 129, 77, 104, 99, 70, 128, 183, 117, 32, 5, 160, 138, 163, 155, 193, 14, 131, 38, 64, 112, 157, 172, 82, 162, 39, 55, 35, 118, 174, 72, 59, 100, 34, 209, 182, 31, 23, 121, 125, 196, 168, 54, 198, 7, 84, 24, 199, 80, 73, 88, 103, 93, 102, 0]], Length: 211\n",
      "Robot Routes: [[[147, 181, 190, 148, 15, 111, 107, 50, 52, 202, 166, 98], [30, 43, 152, 48, 140, 135, 184, 153, 129, 77, 104, 99], [139, 45, 76, 57, 9, 177, 20, 116, 194, 179, 200, 87], [160, 138, 163, 155, 193, 14, 131, 38, 64, 112, 157, 172], [185, 133, 180, 65, 47, 126, 145, 176, 165, 105, 95, 159], [27, 143, 60, 61, 67, 92, 26, 136, 25, 189, 71, 146], [106, 74, 134, 51, 3, 201, 41, 175, 42, 124, 151, 8]]]\n",
      "Route: [0, 85, 81, 113, 170, 4, 62, 94, 130, 37, 40, 141, 119, 101, 79, 204, 178, 108, 58, 49, 149, 208, 197, 203, 6, 56, 164, 206, 171, 89, 122, 66, 63, 29, 46, 185, 159, 27, 146, 123, 22, 83, 156, 11, 161, 2, 33, 191, 188, 86, 68, 158, 139, 87, 18, 13, 10, 169, 19, 96, 195, 36, 115, 1, 44, 142, 16, 187, 75, 120, 167, 137, 147, 98, 53, 90, 192, 205, 12, 207, 114, 21, 144, 132, 127, 186, 91, 97, 173, 17, 78, 109, 110, 106, 8, 28, 69, 150, 154, 30, 99, 70, 128, 183, 117, 32, 5, 160, 172, 82, 162, 39, 55, 35, 118, 174, 72, 59, 100, 34, 209, 182, 31, 23, 121, 125, 196, 168, 54, 198, 7, 84, 24, 199, 80, 73, 88, 103, 93, 102, 0], Robot Group: [[147, 181, 190, 148, 15, 111, 107, 50, 52, 202, 166, 98], [30, 43, 152, 48, 140, 135, 184, 153, 129, 77, 104, 99], [139, 45, 76, 57, 9, 177, 20, 116, 194, 179, 200, 87], [160, 138, 163, 155, 193, 14, 131, 38, 64, 112, 157, 172], [185, 133, 180, 65, 47, 126, 145, 176, 165, 105, 95, 159], [27, 143, 60, 61, 67, 92, 26, 136, 25, 189, 71, 146], [106, 74, 134, 51, 3, 201, 41, 175, 42, 124, 151, 8]]\n",
      "Vehicle 0: 60526 m, 354.985 min, including 38.459 mins waiting time.\n",
      "Total distance of all routes: : 60526 m\n",
      "Maximum travel time: 354.985 min\n",
      "Trial 17...\n",
      "VRP\n",
      "Routes: [[0, 204, 142, 69, 144, 64, 96, 81, 163, 52, 133, 43, 136, 72, 46, 66, 38, 50, 162, 178, 9, 7, 152, 191, 154, 149, 40, 29, 127, 132, 116, 158, 62, 192, 170, 146, 33, 25, 35, 15, 76, 118, 153, 87, 49, 89, 23, 41, 114, 32, 2, 179, 205, 30, 31, 36, 57, 180, 101, 203, 195, 124, 18, 104, 56, 190, 168, 20, 117, 58, 14, 200, 12, 193, 45, 172, 125, 77, 145, 94, 165, 6, 160, 130, 202, 173, 182, 129, 115, 24, 74, 65, 86, 156, 121, 106, 164, 119, 60, 70, 122, 37, 1, 199, 75, 28, 139, 67, 59, 208, 19, 91, 22, 167, 26, 108, 183, 110, 8, 44, 47, 95, 126, 188, 140, 5, 3, 63, 10, 209, 175, 27, 68, 189, 80, 151, 171, 99, 100, 109, 90, 169, 128, 73, 82, 93, 39, 4, 157, 107, 112, 78, 111, 207, 123, 103, 54, 176, 198, 51, 206, 11, 53, 34, 196, 71, 13, 88, 84, 201, 181, 177, 61, 83, 105, 147, 55, 120, 131, 187, 184, 159, 92, 197, 186, 155, 42, 148, 143, 113, 141, 137, 48, 194, 185, 134, 17, 102, 98, 161, 79, 150, 166, 174, 85, 21, 16, 135, 97, 138, 0]], Length: 211\n",
      "Vehicle 0: 72727 m, 492.727 min, including 0 mins waiting time.\n",
      "Total distance of all routes: : 72727 m\n",
      "Maximum travel time: 492.727 min\n",
      "VRP-D\n",
      "Routes: [[0, 204, 142, 69, 144, 64, 96, 81, 163, 52, 133, 43, 136, 72, 46, 66, 38, 50, 162, 178, 9, 7, 152, 191, 154, 149, 40, 29, 127, 132, 116, 158, 62, 192, 170, 146, 33, 25, 35, 15, 76, 118, 153, 87, 49, 89, 23, 41, 114, 32, 2, 179, 205, 30, 31, 36, 57, 180, 101, 203, 195, 124, 18, 104, 56, 190, 168, 20, 117, 58, 14, 200, 12, 193, 45, 172, 125, 77, 145, 94, 165, 6, 160, 130, 202, 173, 182, 129, 115, 24, 74, 65, 86, 156, 121, 106, 164, 119, 60, 70, 122, 37, 1, 199, 75, 28, 139, 67, 59, 208, 19, 91, 22, 167, 26, 108, 183, 110, 8, 44, 47, 95, 126, 188, 140, 5, 3, 63, 10, 209, 175, 27, 68, 189, 80, 151, 171, 99, 100, 109, 90, 169, 128, 73, 82, 93, 39, 4, 157, 107, 112, 78, 111, 207, 123, 103, 54, 176, 198, 51, 206, 11, 53, 34, 196, 71, 13, 88, 84, 201, 181, 177, 61, 83, 105, 147, 55, 120, 131, 187, 184, 159, 92, 197, 186, 155, 42, 148, 143, 113, 141, 137, 48, 194, 185, 134, 17, 102, 98, 161, 79, 150, 166, 174, 85, 21, 16, 135, 97, 138, 0]], Length: 211\n",
      "Vehicle 0: 69877 m, 472.986 min, including 11.109 mins waiting time.\n",
      "Total distance of all routes: : 69877 m\n",
      "Maximum travel time: 472.986 min\n",
      "VRP-R\n",
      "Routes: [[0, 204, 142, 69, 144, 64, 96, 81, 163, 52, 133, 43, 136, 72, 46, 66, 38, 50, 162, 178, 9, 7, 152, 191, 154, 149, 40, 29, 127, 132, 116, 158, 62, 192, 170, 146, 33, 25, 35, 15, 76, 118, 153, 87, 49, 89, 23, 41, 114, 32, 2, 179, 205, 30, 31, 36, 57, 180, 101, 203, 195, 124, 18, 104, 56, 190, 168, 20, 117, 58, 14, 200, 12, 193, 45, 172, 125, 77, 145, 94, 165, 6, 160, 130, 202, 173, 182, 129, 115, 24, 74, 65, 86, 156, 121, 106, 164, 119, 60, 70, 122, 37, 1, 199, 75, 28, 139, 67, 59, 208, 19, 91, 22, 167, 26, 108, 183, 110, 8, 44, 47, 95, 126, 188, 140, 5, 3, 63, 10, 209, 175, 27, 68, 189, 80, 151, 171, 99, 100, 109, 90, 169, 128, 73, 82, 93, 39, 4, 157, 107, 112, 78, 111, 207, 123, 103, 54, 176, 198, 51, 206, 11, 53, 34, 196, 71, 13, 88, 84, 201, 181, 177, 61, 83, 105, 147, 55, 120, 131, 187, 184, 159, 92, 197, 186, 155, 42, 148, 143, 113, 141, 137, 48, 194, 185, 134, 17, 102, 98, 161, 79, 150, 166, 174, 85, 21, 16, 135, 97, 138, 0]], Length: 211\n",
      "Robot Routes: [[[76, 118, 153, 87, 49, 89, 23, 41, 114, 32, 2, 179], [27, 68, 189, 80, 151, 171, 99, 100, 109, 90, 169, 128], [204, 142, 69, 144, 64, 96, 81, 163, 52, 133, 43, 136], [17, 102, 98, 161, 79, 150, 166, 174, 85, 21, 16, 135], [18, 104, 56, 190, 168, 20, 117, 58, 14, 200, 12, 193], [159, 92, 197, 186, 155, 42, 148, 143, 113, 141, 137, 48], [75, 28, 139, 67, 59, 208, 19, 91, 22, 167, 26, 108], [88, 84, 201, 181, 177, 61, 83, 105, 147, 55, 120, 131]]]\n",
      "Route: [0, 204, 136, 72, 46, 66, 38, 50, 162, 178, 9, 7, 152, 191, 154, 149, 40, 29, 127, 132, 116, 158, 62, 192, 170, 146, 33, 25, 35, 15, 76, 179, 205, 30, 31, 36, 57, 180, 101, 203, 195, 124, 18, 193, 45, 172, 125, 77, 145, 94, 165, 6, 160, 130, 202, 173, 182, 129, 115, 24, 74, 65, 86, 156, 121, 106, 164, 119, 60, 70, 122, 37, 1, 199, 75, 108, 183, 110, 8, 44, 47, 95, 126, 188, 140, 5, 3, 63, 10, 209, 175, 27, 128, 73, 82, 93, 39, 4, 157, 107, 112, 78, 111, 207, 123, 103, 54, 176, 198, 51, 206, 11, 53, 34, 196, 71, 13, 88, 131, 187, 184, 159, 48, 194, 185, 134, 17, 135, 97, 138, 0], Robot Group: [[76, 118, 153, 87, 49, 89, 23, 41, 114, 32, 2, 179], [27, 68, 189, 80, 151, 171, 99, 100, 109, 90, 169, 128], [204, 142, 69, 144, 64, 96, 81, 163, 52, 133, 43, 136], [17, 102, 98, 161, 79, 150, 166, 174, 85, 21, 16, 135], [18, 104, 56, 190, 168, 20, 117, 58, 14, 200, 12, 193], [159, 92, 197, 186, 155, 42, 148, 143, 113, 141, 137, 48], [75, 28, 139, 67, 59, 208, 19, 91, 22, 167, 26, 108], [88, 84, 201, 181, 177, 61, 83, 105, 147, 55, 120, 131]]\n",
      "Vehicle 0: 62534 m, 368.071 min, including 45.537 mins waiting time.\n",
      "Total distance of all routes: : 62534 m\n",
      "Maximum travel time: 368.071 min\n",
      "VRP-RD\n",
      "Routes: [[0, 204, 142, 69, 144, 64, 96, 81, 163, 52, 133, 43, 136, 72, 46, 66, 38, 50, 162, 178, 9, 7, 152, 191, 154, 149, 40, 29, 127, 132, 116, 158, 62, 192, 170, 146, 33, 25, 35, 15, 76, 118, 153, 87, 49, 89, 23, 41, 114, 32, 2, 179, 205, 30, 31, 36, 57, 180, 101, 203, 195, 124, 18, 104, 56, 190, 168, 20, 117, 58, 14, 200, 12, 193, 45, 172, 125, 77, 145, 94, 165, 6, 160, 130, 202, 173, 182, 129, 115, 24, 74, 65, 86, 156, 121, 106, 164, 119, 60, 70, 122, 37, 1, 199, 75, 28, 139, 67, 59, 208, 19, 91, 22, 167, 26, 108, 183, 110, 8, 44, 47, 95, 126, 188, 140, 5, 3, 63, 10, 209, 175, 27, 68, 189, 80, 151, 171, 99, 100, 109, 90, 169, 128, 73, 82, 93, 39, 4, 157, 107, 112, 78, 111, 207, 123, 103, 54, 176, 198, 51, 206, 11, 53, 34, 196, 71, 13, 88, 84, 201, 181, 177, 61, 83, 105, 147, 55, 120, 131, 187, 184, 159, 92, 197, 186, 155, 42, 148, 143, 113, 141, 137, 48, 194, 185, 134, 17, 102, 98, 161, 79, 150, 166, 174, 85, 21, 16, 135, 97, 138, 0]], Length: 211\n",
      "Robot Routes: [[[76, 118, 153, 87, 49, 89, 23, 41, 114, 32, 2, 179], [27, 68, 189, 80, 151, 171, 99, 100, 109, 90, 169, 128], [204, 142, 69, 144, 64, 96, 81, 163, 52, 133, 43, 136], [17, 102, 98, 161, 79, 150, 166, 174, 85, 21, 16, 135], [18, 104, 56, 190, 168, 20, 117, 58, 14, 200, 12, 193], [159, 92, 197, 186, 155, 42, 148, 143, 113, 141, 137, 48], [75, 28, 139, 67, 59, 208, 19, 91, 22, 167, 26, 108], [88, 84, 201, 181, 177, 61, 83, 105, 147, 55, 120, 131]]]\n",
      "Route: [0, 204, 136, 72, 46, 66, 38, 50, 162, 178, 9, 7, 152, 191, 154, 149, 40, 29, 127, 132, 116, 158, 62, 192, 170, 146, 33, 25, 35, 15, 76, 179, 205, 30, 31, 36, 57, 180, 101, 203, 195, 124, 18, 193, 45, 172, 125, 77, 145, 94, 165, 6, 160, 130, 202, 173, 182, 129, 115, 24, 74, 65, 86, 156, 121, 106, 164, 119, 60, 70, 122, 37, 1, 199, 75, 108, 183, 110, 8, 44, 47, 95, 126, 188, 140, 5, 3, 63, 10, 209, 175, 27, 128, 73, 82, 93, 39, 4, 157, 107, 112, 78, 111, 207, 123, 103, 54, 176, 198, 51, 206, 11, 53, 34, 196, 71, 13, 88, 131, 187, 184, 159, 48, 194, 185, 134, 17, 135, 97, 138, 0], Robot Group: [[76, 118, 153, 87, 49, 89, 23, 41, 114, 32, 2, 179], [27, 68, 189, 80, 151, 171, 99, 100, 109, 90, 169, 128], [204, 142, 69, 144, 64, 96, 81, 163, 52, 133, 43, 136], [17, 102, 98, 161, 79, 150, 166, 174, 85, 21, 16, 135], [18, 104, 56, 190, 168, 20, 117, 58, 14, 200, 12, 193], [159, 92, 197, 186, 155, 42, 148, 143, 113, 141, 137, 48], [75, 28, 139, 67, 59, 208, 19, 91, 22, 167, 26, 108], [88, 84, 201, 181, 177, 61, 83, 105, 147, 55, 120, 131]]\n",
      "Vehicle 0: 60386 m, 362.233 min, including 59.847 mins waiting time.\n",
      "Total distance of all routes: : 60386 m\n",
      "Maximum travel time: 362.233 min\n",
      "Trial 18...\n",
      "VRP\n",
      "Routes: [[0, 157, 97, 190, 9, 201, 129, 56, 178, 128, 5, 126, 95, 186, 33, 107, 49, 125, 52, 200, 28, 42, 92, 23, 124, 154, 135, 187, 153, 79, 141, 177, 65, 160, 170, 167, 203, 11, 112, 205, 47, 46, 182, 53, 17, 41, 54, 44, 152, 7, 51, 105, 34, 94, 16, 26, 134, 36, 63, 48, 139, 143, 80, 104, 148, 69, 68, 50, 162, 208, 93, 189, 2, 122, 31, 161, 72, 116, 13, 166, 24, 169, 45, 39, 174, 96, 193, 91, 37, 58, 146, 171, 84, 40, 175, 137, 181, 113, 77, 149, 155, 202, 66, 57, 136, 132, 117, 176, 103, 159, 115, 110, 111, 114, 43, 18, 144, 88, 158, 89, 150, 90, 99, 85, 86, 75, 35, 207, 81, 188, 127, 118, 180, 83, 3, 138, 1, 119, 70, 59, 145, 130, 108, 32, 109, 165, 55, 82, 71, 156, 61, 15, 106, 64, 25, 120, 172, 38, 20, 204, 98, 121, 197, 179, 29, 21, 14, 74, 191, 185, 102, 183, 184, 209, 100, 133, 173, 140, 195, 198, 30, 163, 19, 147, 164, 196, 6, 8, 101, 62, 60, 151, 131, 192, 206, 27, 12, 142, 73, 78, 168, 199, 22, 194, 10, 4, 76, 87, 123, 67, 0]], Length: 211\n",
      "Vehicle 0: 73207 m, 493.207 min, including 0 mins waiting time.\n",
      "Total distance of all routes: : 73207 m\n",
      "Maximum travel time: 493.207 min\n",
      "VRP-D\n",
      "Routes: [[0, 157, 97, 190, 9, 201, 129, 56, 178, 128, 5, 126, 95, 186, 33, 107, 49, 125, 52, 200, 28, 42, 92, 23, 124, 154, 135, 187, 153, 79, 141, 177, 65, 160, 170, 167, 203, 11, 112, 205, 47, 46, 182, 53, 17, 41, 54, 44, 152, 7, 51, 105, 34, 94, 16, 26, 134, 36, 63, 48, 139, 143, 80, 104, 148, 69, 68, 50, 162, 208, 93, 189, 2, 122, 31, 161, 72, 116, 13, 166, 24, 169, 45, 39, 174, 96, 193, 91, 37, 58, 146, 171, 84, 40, 175, 137, 181, 113, 77, 149, 155, 202, 66, 57, 136, 132, 117, 176, 103, 159, 115, 110, 111, 114, 43, 18, 144, 88, 158, 89, 150, 90, 99, 85, 86, 75, 35, 207, 81, 188, 127, 118, 180, 83, 3, 138, 1, 119, 70, 59, 145, 130, 108, 32, 109, 165, 55, 82, 71, 156, 61, 15, 106, 64, 25, 120, 172, 38, 20, 204, 98, 121, 197, 179, 29, 21, 14, 74, 191, 185, 102, 183, 184, 209, 100, 133, 173, 140, 195, 198, 30, 163, 19, 147, 164, 196, 6, 8, 101, 62, 60, 151, 131, 192, 206, 27, 12, 142, 73, 78, 168, 199, 22, 194, 10, 4, 76, 87, 123, 67, 0]], Length: 211\n",
      "Vehicle 0: 69518 m, 468.506 min, including 14.988 mins waiting time.\n",
      "Total distance of all routes: : 69518 m\n",
      "Maximum travel time: 468.506 min\n",
      "VRP-R\n",
      "Routes: [[0, 157, 97, 190, 9, 201, 129, 56, 178, 128, 5, 126, 95, 186, 33, 107, 49, 125, 52, 200, 28, 42, 92, 23, 124, 154, 135, 187, 153, 79, 141, 177, 65, 160, 170, 167, 203, 11, 112, 205, 47, 46, 182, 53, 17, 41, 54, 44, 152, 7, 51, 105, 34, 94, 16, 26, 134, 36, 63, 48, 139, 143, 80, 104, 148, 69, 68, 50, 162, 208, 93, 189, 2, 122, 31, 161, 72, 116, 13, 166, 24, 169, 45, 39, 174, 96, 193, 91, 37, 58, 146, 171, 84, 40, 175, 137, 181, 113, 77, 149, 155, 202, 66, 57, 136, 132, 117, 176, 103, 159, 115, 110, 111, 114, 43, 18, 144, 88, 158, 89, 150, 90, 99, 85, 86, 75, 35, 207, 81, 188, 127, 118, 180, 83, 3, 138, 1, 119, 70, 59, 145, 130, 108, 32, 109, 165, 55, 82, 71, 156, 61, 15, 106, 64, 25, 120, 172, 38, 20, 204, 98, 121, 197, 179, 29, 21, 14, 74, 191, 185, 102, 183, 184, 209, 100, 133, 173, 140, 195, 198, 30, 163, 19, 147, 164, 196, 6, 8, 101, 62, 60, 151, 131, 192, 206, 27, 12, 142, 73, 78, 168, 199, 22, 194, 10, 4, 76, 87, 123, 67, 0]], Length: 211\n",
      "Robot Routes: [[[162, 208, 93, 189, 2, 122, 31, 161, 72, 116, 13, 166], [111, 114, 43, 18, 144, 88, 158, 89, 150, 90, 99, 85], [112, 205, 47, 46, 182, 53, 17, 41, 54, 44, 152, 7], [55, 82, 71, 156, 61, 15, 106, 64, 25, 120, 172, 38], [45, 39, 174, 96, 193, 91, 37, 58, 146, 171, 84, 40], [121, 197, 179, 29, 21, 14, 74, 191, 185, 102, 183, 184], [127, 118, 180, 83, 3, 138, 1, 119, 70, 59, 145, 130], [201, 129, 56, 178, 128, 5, 126, 95, 186, 33, 107, 49], [26, 134, 36, 63, 48, 139, 143, 80, 104, 148, 69, 68], [154, 135, 187, 153, 79, 141, 177, 65, 160, 170, 167, 203]]]\n",
      "Route: [0, 157, 97, 190, 9, 201, 49, 125, 52, 200, 28, 42, 92, 23, 124, 154, 203, 11, 112, 7, 51, 105, 34, 94, 16, 26, 68, 50, 162, 166, 24, 169, 45, 40, 175, 137, 181, 113, 77, 149, 155, 202, 66, 57, 136, 132, 117, 176, 103, 159, 115, 110, 111, 85, 86, 75, 35, 207, 81, 188, 127, 130, 108, 32, 109, 165, 55, 38, 20, 204, 98, 121, 184, 209, 100, 133, 173, 140, 195, 198, 30, 163, 19, 147, 164, 196, 6, 8, 101, 62, 60, 151, 131, 192, 206, 27, 12, 142, 73, 78, 168, 199, 22, 194, 10, 4, 76, 87, 123, 67, 0], Robot Group: [[162, 208, 93, 189, 2, 122, 31, 161, 72, 116, 13, 166], [111, 114, 43, 18, 144, 88, 158, 89, 150, 90, 99, 85], [112, 205, 47, 46, 182, 53, 17, 41, 54, 44, 152, 7], [55, 82, 71, 156, 61, 15, 106, 64, 25, 120, 172, 38], [45, 39, 174, 96, 193, 91, 37, 58, 146, 171, 84, 40], [121, 197, 179, 29, 21, 14, 74, 191, 185, 102, 183, 184], [127, 118, 180, 83, 3, 138, 1, 119, 70, 59, 145, 130], [201, 129, 56, 178, 128, 5, 126, 95, 186, 33, 107, 49], [26, 134, 36, 63, 48, 139, 143, 80, 104, 148, 69, 68], [154, 135, 187, 153, 79, 141, 177, 65, 160, 170, 167, 203]]\n",
      "Vehicle 0: 56685 m, 382.158 min, including 105.473 mins waiting time.\n",
      "Total distance of all routes: : 56685 m\n",
      "Maximum travel time: 382.158 min\n",
      "VRP-RD\n",
      "Routes: [[0, 157, 97, 190, 9, 201, 129, 56, 178, 128, 5, 126, 95, 186, 33, 107, 49, 125, 52, 200, 28, 42, 92, 23, 124, 154, 135, 187, 153, 79, 141, 177, 65, 160, 170, 167, 203, 11, 112, 205, 47, 46, 182, 53, 17, 41, 54, 44, 152, 7, 51, 105, 34, 94, 16, 26, 134, 36, 63, 48, 139, 143, 80, 104, 148, 69, 68, 50, 162, 208, 93, 189, 2, 122, 31, 161, 72, 116, 13, 166, 24, 169, 45, 39, 174, 96, 193, 91, 37, 58, 146, 171, 84, 40, 175, 137, 181, 113, 77, 149, 155, 202, 66, 57, 136, 132, 117, 176, 103, 159, 115, 110, 111, 114, 43, 18, 144, 88, 158, 89, 150, 90, 99, 85, 86, 75, 35, 207, 81, 188, 127, 118, 180, 83, 3, 138, 1, 119, 70, 59, 145, 130, 108, 32, 109, 165, 55, 82, 71, 156, 61, 15, 106, 64, 25, 120, 172, 38, 20, 204, 98, 121, 197, 179, 29, 21, 14, 74, 191, 185, 102, 183, 184, 209, 100, 133, 173, 140, 195, 198, 30, 163, 19, 147, 164, 196, 6, 8, 101, 62, 60, 151, 131, 192, 206, 27, 12, 142, 73, 78, 168, 199, 22, 194, 10, 4, 76, 87, 123, 67, 0]], Length: 211\n",
      "Robot Routes: [[[162, 208, 93, 189, 2, 122, 31, 161, 72, 116, 13, 166], [111, 114, 43, 18, 144, 88, 158, 89, 150, 90, 99, 85], [112, 205, 47, 46, 182, 53, 17, 41, 54, 44, 152, 7], [55, 82, 71, 156, 61, 15, 106, 64, 25, 120, 172, 38], [45, 39, 174, 96, 193, 91, 37, 58, 146, 171, 84, 40], [121, 197, 179, 29, 21, 14, 74, 191, 185, 102, 183, 184], [127, 118, 180, 83, 3, 138, 1, 119, 70, 59, 145, 130], [201, 129, 56, 178, 128, 5, 126, 95, 186, 33, 107, 49], [26, 134, 36, 63, 48, 139, 143, 80, 104, 148, 69, 68], [154, 135, 187, 153, 79, 141, 177, 65, 160, 170, 167, 203]]]\n",
      "Route: [0, 157, 97, 190, 9, 201, 49, 125, 52, 200, 28, 42, 92, 23, 124, 154, 203, 11, 112, 7, 51, 105, 34, 94, 16, 26, 68, 50, 162, 166, 24, 169, 45, 40, 175, 137, 181, 113, 77, 149, 155, 202, 66, 57, 136, 132, 117, 176, 103, 159, 115, 110, 111, 85, 86, 75, 35, 207, 81, 188, 127, 130, 108, 32, 109, 165, 55, 38, 20, 204, 98, 121, 184, 209, 100, 133, 173, 140, 195, 198, 30, 163, 19, 147, 164, 196, 6, 8, 101, 62, 60, 151, 131, 192, 206, 27, 12, 142, 73, 78, 168, 199, 22, 194, 10, 4, 76, 87, 123, 67, 0], Robot Group: [[162, 208, 93, 189, 2, 122, 31, 161, 72, 116, 13, 166], [111, 114, 43, 18, 144, 88, 158, 89, 150, 90, 99, 85], [112, 205, 47, 46, 182, 53, 17, 41, 54, 44, 152, 7], [55, 82, 71, 156, 61, 15, 106, 64, 25, 120, 172, 38], [45, 39, 174, 96, 193, 91, 37, 58, 146, 171, 84, 40], [121, 197, 179, 29, 21, 14, 74, 191, 185, 102, 183, 184], [127, 118, 180, 83, 3, 138, 1, 119, 70, 59, 145, 130], [201, 129, 56, 178, 128, 5, 126, 95, 186, 33, 107, 49], [26, 134, 36, 63, 48, 139, 143, 80, 104, 148, 69, 68], [154, 135, 187, 153, 79, 141, 177, 65, 160, 170, 167, 203]]\n",
      "Vehicle 0: 55412 m, 379.959 min, including 120.547 mins waiting time.\n",
      "Total distance of all routes: : 55412 m\n",
      "Maximum travel time: 379.959 min\n",
      "Trial 19...\n",
      "VRP\n",
      "Routes: [[0, 182, 132, 23, 113, 165, 171, 199, 125, 29, 118, 1, 42, 156, 184, 172, 56, 134, 115, 49, 76, 111, 140, 75, 136, 3, 196, 26, 135, 181, 10, 13, 94, 82, 69, 97, 162, 148, 52, 18, 45, 159, 183, 169, 170, 22, 190, 90, 70, 62, 80, 192, 41, 158, 86, 122, 137, 202, 194, 110, 99, 25, 173, 32, 58, 189, 46, 153, 203, 33, 87, 9, 129, 102, 91, 92, 200, 177, 50, 205, 151, 31, 201, 16, 168, 209, 161, 119, 109, 98, 12, 43, 179, 206, 65, 57, 152, 121, 197, 167, 166, 157, 186, 88, 163, 67, 63, 188, 208, 64, 124, 30, 146, 175, 35, 28, 138, 51, 68, 44, 81, 17, 142, 40, 5, 112, 128, 123, 187, 103, 141, 195, 60, 191, 77, 4, 174, 37, 178, 20, 193, 185, 144, 54, 143, 106, 73, 7, 36, 150, 61, 116, 79, 101, 207, 147, 108, 198, 2, 66, 8, 130, 154, 164, 48, 133, 21, 24, 78, 11, 74, 127, 126, 38, 55, 149, 107, 104, 19, 27, 145, 6, 160, 176, 139, 83, 95, 14, 71, 120, 105, 114, 180, 15, 72, 204, 131, 89, 155, 85, 100, 59, 34, 117, 84, 53, 39, 96, 93, 47, 0]], Length: 211\n",
      "Vehicle 0: 71875 m, 491.875 min, including 0 mins waiting time.\n",
      "Total distance of all routes: : 71875 m\n",
      "Maximum travel time: 491.875 min\n",
      "VRP-D\n",
      "Routes: [[0, 182, 132, 23, 113, 165, 171, 199, 125, 29, 118, 1, 42, 156, 184, 172, 56, 134, 115, 49, 76, 111, 140, 75, 136, 3, 196, 26, 135, 181, 10, 13, 94, 82, 69, 97, 162, 148, 52, 18, 45, 159, 183, 169, 170, 22, 190, 90, 70, 62, 80, 192, 41, 158, 86, 122, 137, 202, 194, 110, 99, 25, 173, 32, 58, 189, 46, 153, 203, 33, 87, 9, 129, 102, 91, 92, 200, 177, 50, 205, 151, 31, 201, 16, 168, 209, 161, 119, 109, 98, 12, 43, 179, 206, 65, 57, 152, 121, 197, 167, 166, 157, 186, 88, 163, 67, 63, 188, 208, 64, 124, 30, 146, 175, 35, 28, 138, 51, 68, 44, 81, 17, 142, 40, 5, 112, 128, 123, 187, 103, 141, 195, 60, 191, 77, 4, 174, 37, 178, 20, 193, 185, 144, 54, 143, 106, 73, 7, 36, 150, 61, 116, 79, 101, 207, 147, 108, 198, 2, 66, 8, 130, 154, 164, 48, 133, 21, 24, 78, 11, 74, 127, 126, 38, 55, 149, 107, 104, 19, 27, 145, 6, 160, 176, 139, 83, 95, 14, 71, 120, 105, 114, 180, 15, 72, 204, 131, 89, 155, 85, 100, 59, 34, 117, 84, 53, 39, 96, 93, 47, 0]], Length: 211\n",
      "Vehicle 0: 67290 m, 466.171 min, including 16.881 mins waiting time.\n",
      "Total distance of all routes: : 67290 m\n",
      "Maximum travel time: 466.171 min\n",
      "VRP-R\n",
      "Routes: [[0, 182, 132, 23, 113, 165, 171, 199, 125, 29, 118, 1, 42, 156, 184, 172, 56, 134, 115, 49, 76, 111, 140, 75, 136, 3, 196, 26, 135, 181, 10, 13, 94, 82, 69, 97, 162, 148, 52, 18, 45, 159, 183, 169, 170, 22, 190, 90, 70, 62, 80, 192, 41, 158, 86, 122, 137, 202, 194, 110, 99, 25, 173, 32, 58, 189, 46, 153, 203, 33, 87, 9, 129, 102, 91, 92, 200, 177, 50, 205, 151, 31, 201, 16, 168, 209, 161, 119, 109, 98, 12, 43, 179, 206, 65, 57, 152, 121, 197, 167, 166, 157, 186, 88, 163, 67, 63, 188, 208, 64, 124, 30, 146, 175, 35, 28, 138, 51, 68, 44, 81, 17, 142, 40, 5, 112, 128, 123, 187, 103, 141, 195, 60, 191, 77, 4, 174, 37, 178, 20, 193, 185, 144, 54, 143, 106, 73, 7, 36, 150, 61, 116, 79, 101, 207, 147, 108, 198, 2, 66, 8, 130, 154, 164, 48, 133, 21, 24, 78, 11, 74, 127, 126, 38, 55, 149, 107, 104, 19, 27, 145, 6, 160, 176, 139, 83, 95, 14, 71, 120, 105, 114, 180, 15, 72, 204, 131, 89, 155, 85, 100, 59, 34, 117, 84, 53, 39, 96, 93, 47, 0]], Length: 211\n",
      "Robot Routes: [[[8, 130, 154, 164, 48, 133, 21, 24, 78, 11, 74, 127], [95, 14, 71, 120, 105, 114, 180, 15, 72, 204, 131, 89], [115, 49, 76, 111, 140, 75, 136, 3, 196, 26, 135, 181], [41, 158, 86, 122, 137, 202, 194, 110, 99, 25, 173, 32], [126, 38, 55, 149, 107, 104, 19, 27, 145, 6, 160, 176], [153, 203, 33, 87, 9, 129, 102, 91, 92, 200, 177, 50]]]\n",
      "Route: [0, 182, 132, 23, 113, 165, 171, 199, 125, 29, 118, 1, 42, 156, 184, 172, 56, 134, 115, 181, 10, 13, 94, 82, 69, 97, 162, 148, 52, 18, 45, 159, 183, 169, 170, 22, 190, 90, 70, 62, 80, 192, 41, 32, 58, 189, 46, 153, 50, 205, 151, 31, 201, 16, 168, 209, 161, 119, 109, 98, 12, 43, 179, 206, 65, 57, 152, 121, 197, 167, 166, 157, 186, 88, 163, 67, 63, 188, 208, 64, 124, 30, 146, 175, 35, 28, 138, 51, 68, 44, 81, 17, 142, 40, 5, 112, 128, 123, 187, 103, 141, 195, 60, 191, 77, 4, 174, 37, 178, 20, 193, 185, 144, 54, 143, 106, 73, 7, 36, 150, 61, 116, 79, 101, 207, 147, 108, 198, 2, 66, 8, 127, 126, 176, 139, 83, 95, 89, 155, 85, 100, 59, 34, 117, 84, 53, 39, 96, 93, 47, 0], Robot Group: [[8, 130, 154, 164, 48, 133, 21, 24, 78, 11, 74, 127], [95, 14, 71, 120, 105, 114, 180, 15, 72, 204, 131, 89], [115, 49, 76, 111, 140, 75, 136, 3, 196, 26, 135, 181], [41, 158, 86, 122, 137, 202, 194, 110, 99, 25, 173, 32], [126, 38, 55, 149, 107, 104, 19, 27, 145, 6, 160, 176], [153, 203, 33, 87, 9, 129, 102, 91, 92, 200, 177, 50]]\n",
      "Vehicle 0: 65188 m, 391.425 min, including 26.237 mins waiting time.\n",
      "Total distance of all routes: : 65188 m\n",
      "Maximum travel time: 391.425 min\n",
      "VRP-RD\n",
      "Routes: [[0, 182, 132, 23, 113, 165, 171, 199, 125, 29, 118, 1, 42, 156, 184, 172, 56, 134, 115, 49, 76, 111, 140, 75, 136, 3, 196, 26, 135, 181, 10, 13, 94, 82, 69, 97, 162, 148, 52, 18, 45, 159, 183, 169, 170, 22, 190, 90, 70, 62, 80, 192, 41, 158, 86, 122, 137, 202, 194, 110, 99, 25, 173, 32, 58, 189, 46, 153, 203, 33, 87, 9, 129, 102, 91, 92, 200, 177, 50, 205, 151, 31, 201, 16, 168, 209, 161, 119, 109, 98, 12, 43, 179, 206, 65, 57, 152, 121, 197, 167, 166, 157, 186, 88, 163, 67, 63, 188, 208, 64, 124, 30, 146, 175, 35, 28, 138, 51, 68, 44, 81, 17, 142, 40, 5, 112, 128, 123, 187, 103, 141, 195, 60, 191, 77, 4, 174, 37, 178, 20, 193, 185, 144, 54, 143, 106, 73, 7, 36, 150, 61, 116, 79, 101, 207, 147, 108, 198, 2, 66, 8, 130, 154, 164, 48, 133, 21, 24, 78, 11, 74, 127, 126, 38, 55, 149, 107, 104, 19, 27, 145, 6, 160, 176, 139, 83, 95, 14, 71, 120, 105, 114, 180, 15, 72, 204, 131, 89, 155, 85, 100, 59, 34, 117, 84, 53, 39, 96, 93, 47, 0]], Length: 211\n",
      "Robot Routes: [[[8, 130, 154, 164, 48, 133, 21, 24, 78, 11, 74, 127], [95, 14, 71, 120, 105, 114, 180, 15, 72, 204, 131, 89], [115, 49, 76, 111, 140, 75, 136, 3, 196, 26, 135, 181], [41, 158, 86, 122, 137, 202, 194, 110, 99, 25, 173, 32], [126, 38, 55, 149, 107, 104, 19, 27, 145, 6, 160, 176], [153, 203, 33, 87, 9, 129, 102, 91, 92, 200, 177, 50]]]\n",
      "Route: [0, 182, 132, 23, 113, 165, 171, 199, 125, 29, 118, 1, 42, 156, 184, 172, 56, 134, 115, 181, 10, 13, 94, 82, 69, 97, 162, 148, 52, 18, 45, 159, 183, 169, 170, 22, 190, 90, 70, 62, 80, 192, 41, 32, 58, 189, 46, 153, 50, 205, 151, 31, 201, 16, 168, 209, 161, 119, 109, 98, 12, 43, 179, 206, 65, 57, 152, 121, 197, 167, 166, 157, 186, 88, 163, 67, 63, 188, 208, 64, 124, 30, 146, 175, 35, 28, 138, 51, 68, 44, 81, 17, 142, 40, 5, 112, 128, 123, 187, 103, 141, 195, 60, 191, 77, 4, 174, 37, 178, 20, 193, 185, 144, 54, 143, 106, 73, 7, 36, 150, 61, 116, 79, 101, 207, 147, 108, 198, 2, 66, 8, 127, 126, 176, 139, 83, 95, 89, 155, 85, 100, 59, 34, 117, 84, 53, 39, 96, 93, 47, 0], Robot Group: [[8, 130, 154, 164, 48, 133, 21, 24, 78, 11, 74, 127], [95, 14, 71, 120, 105, 114, 180, 15, 72, 204, 131, 89], [115, 49, 76, 111, 140, 75, 136, 3, 196, 26, 135, 181], [41, 158, 86, 122, 137, 202, 194, 110, 99, 25, 173, 32], [126, 38, 55, 149, 107, 104, 19, 27, 145, 6, 160, 176], [153, 203, 33, 87, 9, 129, 102, 91, 92, 200, 177, 50]]\n",
      "Vehicle 0: 61297 m, 373.878 min, including 40.581 mins waiting time.\n",
      "Total distance of all routes: : 61297 m\n",
      "Maximum travel time: 373.878 min\n",
      "Trial 20...\n",
      "VRP\n",
      "Routes: [[0, 120, 106, 9, 20, 103, 40, 181, 115, 87, 25, 72, 177, 69, 150, 8, 166, 135, 7, 71, 46, 209, 107, 179, 152, 86, 53, 144, 133, 190, 145, 129, 205, 132, 47, 18, 75, 17, 138, 199, 185, 33, 2, 38, 68, 104, 37, 143, 206, 97, 202, 34, 128, 36, 59, 32, 4, 176, 163, 41, 48, 157, 11, 203, 35, 127, 64, 151, 3, 198, 142, 61, 6, 76, 194, 89, 1, 84, 91, 109, 92, 195, 169, 67, 164, 98, 102, 130, 170, 94, 83, 54, 189, 23, 125, 200, 78, 44, 124, 165, 66, 79, 122, 105, 108, 183, 51, 55, 100, 52, 174, 88, 131, 111, 26, 74, 162, 140, 10, 65, 149, 182, 155, 99, 171, 187, 112, 82, 123, 63, 146, 191, 136, 161, 121, 13, 113, 180, 29, 116, 172, 126, 93, 101, 73, 173, 154, 50, 168, 196, 156, 114, 70, 184, 192, 178, 19, 137, 186, 139, 60, 159, 77, 95, 42, 21, 197, 110, 27, 62, 24, 58, 31, 14, 96, 134, 57, 30, 49, 22, 90, 158, 15, 118, 119, 160, 5, 16, 167, 43, 56, 81, 207, 80, 153, 201, 204, 147, 12, 175, 28, 85, 45, 39, 148, 117, 188, 208, 193, 141, 0]], Length: 211\n",
      "Vehicle 0: 72814 m, 492.814 min, including 0 mins waiting time.\n",
      "Total distance of all routes: : 72814 m\n",
      "Maximum travel time: 492.814 min\n",
      "VRP-D\n",
      "Routes: [[0, 120, 106, 9, 20, 103, 40, 181, 115, 87, 25, 72, 177, 69, 150, 8, 166, 135, 7, 71, 46, 209, 107, 179, 152, 86, 53, 144, 133, 190, 145, 129, 205, 132, 47, 18, 75, 17, 138, 199, 185, 33, 2, 38, 68, 104, 37, 143, 206, 97, 202, 34, 128, 36, 59, 32, 4, 176, 163, 41, 48, 157, 11, 203, 35, 127, 64, 151, 3, 198, 142, 61, 6, 76, 194, 89, 1, 84, 91, 109, 92, 195, 169, 67, 164, 98, 102, 130, 170, 94, 83, 54, 189, 23, 125, 200, 78, 44, 124, 165, 66, 79, 122, 105, 108, 183, 51, 55, 100, 52, 174, 88, 131, 111, 26, 74, 162, 140, 10, 65, 149, 182, 155, 99, 171, 187, 112, 82, 123, 63, 146, 191, 136, 161, 121, 13, 113, 180, 29, 116, 172, 126, 93, 101, 73, 173, 154, 50, 168, 196, 156, 114, 70, 184, 192, 178, 19, 137, 186, 139, 60, 159, 77, 95, 42, 21, 197, 110, 27, 62, 24, 58, 31, 14, 96, 134, 57, 30, 49, 22, 90, 158, 15, 118, 119, 160, 5, 16, 167, 43, 56, 81, 207, 80, 153, 201, 204, 147, 12, 175, 28, 85, 45, 39, 148, 117, 188, 208, 193, 141, 0]], Length: 211\n",
      "Vehicle 0: 69789 m, 470.815 min, including 13.026 mins waiting time.\n",
      "Total distance of all routes: : 69789 m\n",
      "Maximum travel time: 470.815 min\n",
      "VRP-R\n",
      "Routes: [[0, 120, 106, 9, 20, 103, 40, 181, 115, 87, 25, 72, 177, 69, 150, 8, 166, 135, 7, 71, 46, 209, 107, 179, 152, 86, 53, 144, 133, 190, 145, 129, 205, 132, 47, 18, 75, 17, 138, 199, 185, 33, 2, 38, 68, 104, 37, 143, 206, 97, 202, 34, 128, 36, 59, 32, 4, 176, 163, 41, 48, 157, 11, 203, 35, 127, 64, 151, 3, 198, 142, 61, 6, 76, 194, 89, 1, 84, 91, 109, 92, 195, 169, 67, 164, 98, 102, 130, 170, 94, 83, 54, 189, 23, 125, 200, 78, 44, 124, 165, 66, 79, 122, 105, 108, 183, 51, 55, 100, 52, 174, 88, 131, 111, 26, 74, 162, 140, 10, 65, 149, 182, 155, 99, 171, 187, 112, 82, 123, 63, 146, 191, 136, 161, 121, 13, 113, 180, 29, 116, 172, 126, 93, 101, 73, 173, 154, 50, 168, 196, 156, 114, 70, 184, 192, 178, 19, 137, 186, 139, 60, 159, 77, 95, 42, 21, 197, 110, 27, 62, 24, 58, 31, 14, 96, 134, 57, 30, 49, 22, 90, 158, 15, 118, 119, 160, 5, 16, 167, 43, 56, 81, 207, 80, 153, 201, 204, 147, 12, 175, 28, 85, 45, 39, 148, 117, 188, 208, 193, 141, 0]], Length: 211\n",
      "Robot Routes: [[[0, 120, 106, 9, 20, 103, 40, 181, 115, 87, 25, 72], [154, 50, 168, 196, 156, 114, 70, 184, 192, 178, 19, 137], [111, 26, 74, 162, 140, 10, 65, 149, 182, 155, 99, 171], [48, 157, 11, 203, 35, 127, 64, 151, 3, 198, 142, 61], [76, 194, 89, 1, 84, 91, 109, 92, 195, 169, 67, 164], [54, 189, 23, 125, 200, 78, 44, 124, 165, 66, 79, 122], [138, 199, 185, 33, 2, 38, 68, 104, 37, 143, 206, 97], [166, 135, 7, 71, 46, 209, 107, 179, 152, 86, 53, 144]]]\n",
      "Route: [0, 72, 177, 69, 150, 8, 166, 144, 133, 190, 145, 129, 205, 132, 47, 18, 75, 17, 138, 97, 202, 34, 128, 36, 59, 32, 4, 176, 163, 41, 48, 61, 6, 76, 164, 98, 102, 130, 170, 94, 83, 54, 122, 105, 108, 183, 51, 55, 100, 52, 174, 88, 131, 111, 171, 187, 112, 82, 123, 63, 146, 191, 136, 161, 121, 13, 113, 180, 29, 116, 172, 126, 93, 101, 73, 173, 154, 137, 186, 139, 60, 159, 77, 95, 42, 21, 197, 110, 27, 62, 24, 58, 31, 14, 96, 134, 57, 30, 49, 22, 90, 158, 15, 118, 119, 160, 5, 16, 167, 43, 56, 81, 207, 80, 153, 201, 204, 147, 12, 175, 28, 85, 45, 39, 148, 117, 188, 208, 193, 141, 0], Robot Group: [[0, 120, 106, 9, 20, 103, 40, 181, 115, 87, 25, 72], [154, 50, 168, 196, 156, 114, 70, 184, 192, 178, 19, 137], [111, 26, 74, 162, 140, 10, 65, 149, 182, 155, 99, 171], [48, 157, 11, 203, 35, 127, 64, 151, 3, 198, 142, 61], [76, 194, 89, 1, 84, 91, 109, 92, 195, 169, 67, 164], [54, 189, 23, 125, 200, 78, 44, 124, 165, 66, 79, 122], [138, 199, 185, 33, 2, 38, 68, 104, 37, 143, 206, 97], [166, 135, 7, 71, 46, 209, 107, 179, 152, 86, 53, 144]]\n",
      "Vehicle 0: 62557 m, 360.544 min, including 37.987 mins waiting time.\n",
      "Total distance of all routes: : 62557 m\n",
      "Maximum travel time: 360.544 min\n",
      "VRP-RD\n",
      "Routes: [[0, 120, 106, 9, 20, 103, 40, 181, 115, 87, 25, 72, 177, 69, 150, 8, 166, 135, 7, 71, 46, 209, 107, 179, 152, 86, 53, 144, 133, 190, 145, 129, 205, 132, 47, 18, 75, 17, 138, 199, 185, 33, 2, 38, 68, 104, 37, 143, 206, 97, 202, 34, 128, 36, 59, 32, 4, 176, 163, 41, 48, 157, 11, 203, 35, 127, 64, 151, 3, 198, 142, 61, 6, 76, 194, 89, 1, 84, 91, 109, 92, 195, 169, 67, 164, 98, 102, 130, 170, 94, 83, 54, 189, 23, 125, 200, 78, 44, 124, 165, 66, 79, 122, 105, 108, 183, 51, 55, 100, 52, 174, 88, 131, 111, 26, 74, 162, 140, 10, 65, 149, 182, 155, 99, 171, 187, 112, 82, 123, 63, 146, 191, 136, 161, 121, 13, 113, 180, 29, 116, 172, 126, 93, 101, 73, 173, 154, 50, 168, 196, 156, 114, 70, 184, 192, 178, 19, 137, 186, 139, 60, 159, 77, 95, 42, 21, 197, 110, 27, 62, 24, 58, 31, 14, 96, 134, 57, 30, 49, 22, 90, 158, 15, 118, 119, 160, 5, 16, 167, 43, 56, 81, 207, 80, 153, 201, 204, 147, 12, 175, 28, 85, 45, 39, 148, 117, 188, 208, 193, 141, 0]], Length: 211\n",
      "Robot Routes: [[[0, 120, 106, 9, 20, 103, 40, 181, 115, 87, 25, 72], [154, 50, 168, 196, 156, 114, 70, 184, 192, 178, 19, 137], [111, 26, 74, 162, 140, 10, 65, 149, 182, 155, 99, 171], [48, 157, 11, 203, 35, 127, 64, 151, 3, 198, 142, 61], [76, 194, 89, 1, 84, 91, 109, 92, 195, 169, 67, 164], [54, 189, 23, 125, 200, 78, 44, 124, 165, 66, 79, 122], [138, 199, 185, 33, 2, 38, 68, 104, 37, 143, 206, 97], [166, 135, 7, 71, 46, 209, 107, 179, 152, 86, 53, 144]]]\n",
      "Route: [0, 72, 177, 69, 150, 8, 166, 144, 133, 190, 145, 129, 205, 132, 47, 18, 75, 17, 138, 97, 202, 34, 128, 36, 59, 32, 4, 176, 163, 41, 48, 61, 6, 76, 164, 98, 102, 130, 170, 94, 83, 54, 122, 105, 108, 183, 51, 55, 100, 52, 174, 88, 131, 111, 171, 187, 112, 82, 123, 63, 146, 191, 136, 161, 121, 13, 113, 180, 29, 116, 172, 126, 93, 101, 73, 173, 154, 137, 186, 139, 60, 159, 77, 95, 42, 21, 197, 110, 27, 62, 24, 58, 31, 14, 96, 134, 57, 30, 49, 22, 90, 158, 15, 118, 119, 160, 5, 16, 167, 43, 56, 81, 207, 80, 153, 201, 204, 147, 12, 175, 28, 85, 45, 39, 148, 117, 188, 208, 193, 141, 0], Robot Group: [[0, 120, 106, 9, 20, 103, 40, 181, 115, 87, 25, 72], [154, 50, 168, 196, 156, 114, 70, 184, 192, 178, 19, 137], [111, 26, 74, 162, 140, 10, 65, 149, 182, 155, 99, 171], [48, 157, 11, 203, 35, 127, 64, 151, 3, 198, 142, 61], [76, 194, 89, 1, 84, 91, 109, 92, 195, 169, 67, 164], [54, 189, 23, 125, 200, 78, 44, 124, 165, 66, 79, 122], [138, 199, 185, 33, 2, 38, 68, 104, 37, 143, 206, 97], [166, 135, 7, 71, 46, 209, 107, 179, 152, 86, 53, 144]]\n",
      "Vehicle 0: 61258 m, 351.05 min, including 51.792 mins waiting time.\n",
      "Total distance of all routes: : 61258 m\n",
      "Maximum travel time: 351.05 min\n",
      "Trial 21...\n",
      "VRP\n",
      "Routes: [[0, 125, 114, 69, 182, 66, 120, 20, 29, 8, 71, 207, 161, 68, 165, 131, 171, 193, 156, 45, 166, 21, 13, 36, 5, 76, 49, 27, 175, 4, 97, 208, 153, 40, 155, 1, 126, 58, 140, 185, 197, 187, 158, 6, 54, 128, 85, 52, 51, 110, 25, 98, 169, 33, 164, 62, 149, 105, 154, 32, 79, 206, 191, 150, 100, 57, 170, 10, 122, 174, 61, 162, 137, 136, 190, 167, 64, 209, 117, 118, 92, 38, 189, 90, 7, 115, 200, 93, 203, 199, 163, 91, 111, 116, 55, 56, 30, 106, 177, 147, 48, 63, 39, 75, 176, 195, 73, 205, 135, 74, 103, 15, 102, 184, 87, 12, 17, 141, 28, 82, 101, 41, 181, 108, 121, 26, 46, 133, 95, 70, 18, 43, 145, 157, 173, 72, 96, 151, 144, 44, 86, 188, 47, 139, 50, 104, 168, 196, 194, 60, 201, 152, 127, 77, 81, 180, 146, 132, 124, 142, 198, 2, 192, 3, 65, 53, 88, 78, 202, 22, 94, 112, 31, 119, 11, 134, 35, 204, 9, 178, 84, 148, 159, 42, 89, 172, 99, 24, 143, 130, 16, 34, 138, 160, 23, 19, 129, 186, 183, 59, 83, 109, 37, 80, 179, 14, 107, 123, 113, 67, 0]], Length: 211\n",
      "Vehicle 0: 69072 m, 489.072 min, including 0 mins waiting time.\n",
      "Total distance of all routes: : 69072 m\n",
      "Maximum travel time: 489.072 min\n",
      "VRP-D\n",
      "Routes: [[0, 125, 114, 69, 182, 66, 120, 20, 29, 8, 71, 207, 161, 68, 165, 131, 171, 193, 156, 45, 166, 21, 13, 36, 5, 76, 49, 27, 175, 4, 97, 208, 153, 40, 155, 1, 126, 58, 140, 185, 197, 187, 158, 6, 54, 128, 85, 52, 51, 110, 25, 98, 169, 33, 164, 62, 149, 105, 154, 32, 79, 206, 191, 150, 100, 57, 170, 10, 122, 174, 61, 162, 137, 136, 190, 167, 64, 209, 117, 118, 92, 38, 189, 90, 7, 115, 200, 93, 203, 199, 163, 91, 111, 116, 55, 56, 30, 106, 177, 147, 48, 63, 39, 75, 176, 195, 73, 205, 135, 74, 103, 15, 102, 184, 87, 12, 17, 141, 28, 82, 101, 41, 181, 108, 121, 26, 46, 133, 95, 70, 18, 43, 145, 157, 173, 72, 96, 151, 144, 44, 86, 188, 47, 139, 50, 104, 168, 196, 194, 60, 201, 152, 127, 77, 81, 180, 146, 132, 124, 142, 198, 2, 192, 3, 65, 53, 88, 78, 202, 22, 94, 112, 31, 119, 11, 134, 35, 204, 9, 178, 84, 148, 159, 42, 89, 172, 99, 24, 143, 130, 16, 34, 138, 160, 23, 19, 129, 186, 183, 59, 83, 109, 37, 80, 179, 14, 107, 123, 113, 67, 0]], Length: 211\n",
      "Vehicle 0: 66323 m, 465.661 min, including 13.338 mins waiting time.\n",
      "Total distance of all routes: : 66323 m\n",
      "Maximum travel time: 465.661 min\n",
      "VRP-R\n",
      "Routes: [[0, 125, 114, 69, 182, 66, 120, 20, 29, 8, 71, 207, 161, 68, 165, 131, 171, 193, 156, 45, 166, 21, 13, 36, 5, 76, 49, 27, 175, 4, 97, 208, 153, 40, 155, 1, 126, 58, 140, 185, 197, 187, 158, 6, 54, 128, 85, 52, 51, 110, 25, 98, 169, 33, 164, 62, 149, 105, 154, 32, 79, 206, 191, 150, 100, 57, 170, 10, 122, 174, 61, 162, 137, 136, 190, 167, 64, 209, 117, 118, 92, 38, 189, 90, 7, 115, 200, 93, 203, 199, 163, 91, 111, 116, 55, 56, 30, 106, 177, 147, 48, 63, 39, 75, 176, 195, 73, 205, 135, 74, 103, 15, 102, 184, 87, 12, 17, 141, 28, 82, 101, 41, 181, 108, 121, 26, 46, 133, 95, 70, 18, 43, 145, 157, 173, 72, 96, 151, 144, 44, 86, 188, 47, 139, 50, 104, 168, 196, 194, 60, 201, 152, 127, 77, 81, 180, 146, 132, 124, 142, 198, 2, 192, 3, 65, 53, 88, 78, 202, 22, 94, 112, 31, 119, 11, 134, 35, 204, 9, 178, 84, 148, 159, 42, 89, 172, 99, 24, 143, 130, 16, 34, 138, 160, 23, 19, 129, 186, 183, 59, 83, 109, 37, 80, 179, 14, 107, 123, 113, 67, 0]], Length: 211\n",
      "Robot Routes: [[[51, 110, 25, 98, 169, 33, 164, 62, 149, 105, 154, 32], [143, 130, 16, 34, 138, 160, 23, 19, 129, 186, 183, 59], [0, 125, 114, 69, 182, 66, 120, 20, 29, 8, 71, 207], [81, 180, 146, 132, 124, 142, 198, 2, 192, 3, 65, 53], [166, 21, 13, 36, 5, 76, 49, 27, 175, 4, 97, 208], [57, 170, 10, 122, 174, 61, 162, 137, 136, 190, 167, 64]]]\n",
      "Route: [0, 207, 161, 68, 165, 131, 171, 193, 156, 45, 166, 208, 153, 40, 155, 1, 126, 58, 140, 185, 197, 187, 158, 6, 54, 128, 85, 52, 51, 32, 79, 206, 191, 150, 100, 57, 64, 209, 117, 118, 92, 38, 189, 90, 7, 115, 200, 93, 203, 199, 163, 91, 111, 116, 55, 56, 30, 106, 177, 147, 48, 63, 39, 75, 176, 195, 73, 205, 135, 74, 103, 15, 102, 184, 87, 12, 17, 141, 28, 82, 101, 41, 181, 108, 121, 26, 46, 133, 95, 70, 18, 43, 145, 157, 173, 72, 96, 151, 144, 44, 86, 188, 47, 139, 50, 104, 168, 196, 194, 60, 201, 152, 127, 77, 81, 53, 88, 78, 202, 22, 94, 112, 31, 119, 11, 134, 35, 204, 9, 178, 84, 148, 159, 42, 89, 172, 99, 24, 143, 59, 83, 109, 37, 80, 179, 14, 107, 123, 113, 67, 0], Robot Group: [[51, 110, 25, 98, 169, 33, 164, 62, 149, 105, 154, 32], [143, 130, 16, 34, 138, 160, 23, 19, 129, 186, 183, 59], [0, 125, 114, 69, 182, 66, 120, 20, 29, 8, 71, 207], [81, 180, 146, 132, 124, 142, 198, 2, 192, 3, 65, 53], [166, 21, 13, 36, 5, 76, 49, 27, 175, 4, 97, 208], [57, 170, 10, 122, 174, 61, 162, 137, 136, 190, 167, 64]]\n",
      "Vehicle 0: 61903 m, 401.457 min, including 39.554 mins waiting time.\n",
      "Total distance of all routes: : 61903 m\n",
      "Maximum travel time: 401.457 min\n",
      "VRP-RD\n",
      "Routes: [[0, 125, 114, 69, 182, 66, 120, 20, 29, 8, 71, 207, 161, 68, 165, 131, 171, 193, 156, 45, 166, 21, 13, 36, 5, 76, 49, 27, 175, 4, 97, 208, 153, 40, 155, 1, 126, 58, 140, 185, 197, 187, 158, 6, 54, 128, 85, 52, 51, 110, 25, 98, 169, 33, 164, 62, 149, 105, 154, 32, 79, 206, 191, 150, 100, 57, 170, 10, 122, 174, 61, 162, 137, 136, 190, 167, 64, 209, 117, 118, 92, 38, 189, 90, 7, 115, 200, 93, 203, 199, 163, 91, 111, 116, 55, 56, 30, 106, 177, 147, 48, 63, 39, 75, 176, 195, 73, 205, 135, 74, 103, 15, 102, 184, 87, 12, 17, 141, 28, 82, 101, 41, 181, 108, 121, 26, 46, 133, 95, 70, 18, 43, 145, 157, 173, 72, 96, 151, 144, 44, 86, 188, 47, 139, 50, 104, 168, 196, 194, 60, 201, 152, 127, 77, 81, 180, 146, 132, 124, 142, 198, 2, 192, 3, 65, 53, 88, 78, 202, 22, 94, 112, 31, 119, 11, 134, 35, 204, 9, 178, 84, 148, 159, 42, 89, 172, 99, 24, 143, 130, 16, 34, 138, 160, 23, 19, 129, 186, 183, 59, 83, 109, 37, 80, 179, 14, 107, 123, 113, 67, 0]], Length: 211\n",
      "Robot Routes: [[[51, 110, 25, 98, 169, 33, 164, 62, 149, 105, 154, 32], [143, 130, 16, 34, 138, 160, 23, 19, 129, 186, 183, 59], [0, 125, 114, 69, 182, 66, 120, 20, 29, 8, 71, 207], [81, 180, 146, 132, 124, 142, 198, 2, 192, 3, 65, 53], [166, 21, 13, 36, 5, 76, 49, 27, 175, 4, 97, 208], [57, 170, 10, 122, 174, 61, 162, 137, 136, 190, 167, 64]]]\n",
      "Route: [0, 207, 161, 68, 165, 131, 171, 193, 156, 45, 166, 208, 153, 40, 155, 1, 126, 58, 140, 185, 197, 187, 158, 6, 54, 128, 85, 52, 51, 32, 79, 206, 191, 150, 100, 57, 64, 209, 117, 118, 92, 38, 189, 90, 7, 115, 200, 93, 203, 199, 163, 91, 111, 116, 55, 56, 30, 106, 177, 147, 48, 63, 39, 75, 176, 195, 73, 205, 135, 74, 103, 15, 102, 184, 87, 12, 17, 141, 28, 82, 101, 41, 181, 108, 121, 26, 46, 133, 95, 70, 18, 43, 145, 157, 173, 72, 96, 151, 144, 44, 86, 188, 47, 139, 50, 104, 168, 196, 194, 60, 201, 152, 127, 77, 81, 53, 88, 78, 202, 22, 94, 112, 31, 119, 11, 134, 35, 204, 9, 178, 84, 148, 159, 42, 89, 172, 99, 24, 143, 59, 83, 109, 37, 80, 179, 14, 107, 123, 113, 67, 0], Robot Group: [[51, 110, 25, 98, 169, 33, 164, 62, 149, 105, 154, 32], [143, 130, 16, 34, 138, 160, 23, 19, 129, 186, 183, 59], [0, 125, 114, 69, 182, 66, 120, 20, 29, 8, 71, 207], [81, 180, 146, 132, 124, 142, 198, 2, 192, 3, 65, 53], [166, 21, 13, 36, 5, 76, 49, 27, 175, 4, 97, 208], [57, 170, 10, 122, 174, 61, 162, 137, 136, 190, 167, 64]]\n",
      "Vehicle 0: 59886 m, 385.944 min, including 50.058 mins waiting time.\n",
      "Total distance of all routes: : 59886 m\n",
      "Maximum travel time: 385.944 min\n",
      "Trial 22...\n",
      "VRP\n",
      "Routes: [[0, 189, 158, 195, 178, 203, 115, 76, 9, 73, 169, 168, 52, 117, 2, 177, 97, 129, 183, 143, 50, 190, 56, 98, 121, 35, 32, 187, 164, 54, 36, 6, 157, 85, 126, 107, 200, 104, 196, 159, 43, 19, 184, 209, 137, 124, 17, 127, 20, 175, 58, 131, 88, 44, 51, 135, 47, 186, 69, 42, 103, 155, 120, 176, 113, 89, 166, 171, 206, 60, 198, 149, 108, 46, 70, 140, 40, 90, 38, 49, 57, 191, 119, 170, 33, 80, 110, 147, 139, 133, 77, 202, 188, 87, 99, 146, 8, 141, 91, 66, 67, 23, 68, 86, 1, 37, 109, 61, 145, 48, 71, 185, 128, 172, 22, 134, 4, 174, 72, 180, 106, 3, 118, 55, 12, 31, 16, 82, 24, 138, 152, 148, 123, 192, 151, 64, 193, 162, 173, 130, 14, 92, 204, 114, 111, 84, 205, 7, 27, 25, 153, 93, 112, 53, 28, 208, 144, 122, 45, 74, 78, 94, 101, 34, 39, 5, 165, 83, 59, 142, 30, 62, 75, 18, 79, 102, 100, 207, 65, 199, 63, 96, 15, 163, 156, 179, 11, 182, 116, 161, 132, 160, 150, 26, 81, 197, 41, 154, 181, 21, 95, 194, 105, 136, 10, 167, 13, 29, 201, 125, 0]], Length: 211\n",
      "Vehicle 0: 70958 m, 490.958 min, including 0 mins waiting time.\n",
      "Total distance of all routes: : 70958 m\n",
      "Maximum travel time: 490.958 min\n",
      "VRP-D\n",
      "Routes: [[0, 189, 158, 195, 178, 203, 115, 76, 9, 73, 169, 168, 52, 117, 2, 177, 97, 129, 183, 143, 50, 190, 56, 98, 121, 35, 32, 187, 164, 54, 36, 6, 157, 85, 126, 107, 200, 104, 196, 159, 43, 19, 184, 209, 137, 124, 17, 127, 20, 175, 58, 131, 88, 44, 51, 135, 47, 186, 69, 42, 103, 155, 120, 176, 113, 89, 166, 171, 206, 60, 198, 149, 108, 46, 70, 140, 40, 90, 38, 49, 57, 191, 119, 170, 33, 80, 110, 147, 139, 133, 77, 202, 188, 87, 99, 146, 8, 141, 91, 66, 67, 23, 68, 86, 1, 37, 109, 61, 145, 48, 71, 185, 128, 172, 22, 134, 4, 174, 72, 180, 106, 3, 118, 55, 12, 31, 16, 82, 24, 138, 152, 148, 123, 192, 151, 64, 193, 162, 173, 130, 14, 92, 204, 114, 111, 84, 205, 7, 27, 25, 153, 93, 112, 53, 28, 208, 144, 122, 45, 74, 78, 94, 101, 34, 39, 5, 165, 83, 59, 142, 30, 62, 75, 18, 79, 102, 100, 207, 65, 199, 63, 96, 15, 163, 156, 179, 11, 182, 116, 161, 132, 160, 150, 26, 81, 197, 41, 154, 181, 21, 95, 194, 105, 136, 10, 167, 13, 29, 201, 125, 0]], Length: 211\n",
      "Vehicle 0: 69325 m, 469.48 min, including 12.155 mins waiting time.\n",
      "Total distance of all routes: : 69325 m\n",
      "Maximum travel time: 469.48 min\n",
      "VRP-R\n",
      "Routes: [[0, 189, 158, 195, 178, 203, 115, 76, 9, 73, 169, 168, 52, 117, 2, 177, 97, 129, 183, 143, 50, 190, 56, 98, 121, 35, 32, 187, 164, 54, 36, 6, 157, 85, 126, 107, 200, 104, 196, 159, 43, 19, 184, 209, 137, 124, 17, 127, 20, 175, 58, 131, 88, 44, 51, 135, 47, 186, 69, 42, 103, 155, 120, 176, 113, 89, 166, 171, 206, 60, 198, 149, 108, 46, 70, 140, 40, 90, 38, 49, 57, 191, 119, 170, 33, 80, 110, 147, 139, 133, 77, 202, 188, 87, 99, 146, 8, 141, 91, 66, 67, 23, 68, 86, 1, 37, 109, 61, 145, 48, 71, 185, 128, 172, 22, 134, 4, 174, 72, 180, 106, 3, 118, 55, 12, 31, 16, 82, 24, 138, 152, 148, 123, 192, 151, 64, 193, 162, 173, 130, 14, 92, 204, 114, 111, 84, 205, 7, 27, 25, 153, 93, 112, 53, 28, 208, 144, 122, 45, 74, 78, 94, 101, 34, 39, 5, 165, 83, 59, 142, 30, 62, 75, 18, 79, 102, 100, 207, 65, 199, 63, 96, 15, 163, 156, 179, 11, 182, 116, 161, 132, 160, 150, 26, 81, 197, 41, 154, 181, 21, 95, 194, 105, 136, 10, 167, 13, 29, 201, 125, 0]], Length: 211\n",
      "Robot Routes: [[[93, 112, 53, 28, 208, 144, 122, 45, 74, 78, 94, 101], [173, 130, 14, 92, 204, 114, 111, 84, 205, 7, 27, 25], [97, 129, 183, 143, 50, 190, 56, 98, 121, 35, 32, 187], [80, 110, 147, 139, 133, 77, 202, 188, 87, 99, 146, 8], [209, 137, 124, 17, 127, 20, 175, 58, 131, 88, 44, 51], [149, 108, 46, 70, 140, 40, 90, 38, 49, 57, 191, 119], [181, 21, 95, 194, 105, 136, 10, 167, 13, 29, 201, 125], [102, 100, 207, 65, 199, 63, 96, 15, 163, 156, 179, 11], [3, 118, 55, 12, 31, 16, 82, 24, 138, 152, 148, 123]]]\n",
      "Route: [0, 189, 158, 195, 178, 203, 115, 76, 9, 73, 169, 168, 52, 117, 2, 177, 97, 187, 164, 54, 36, 6, 157, 85, 126, 107, 200, 104, 196, 159, 43, 19, 184, 209, 51, 135, 47, 186, 69, 42, 103, 155, 120, 176, 113, 89, 166, 171, 206, 60, 198, 149, 119, 170, 33, 80, 8, 141, 91, 66, 67, 23, 68, 86, 1, 37, 109, 61, 145, 48, 71, 185, 128, 172, 22, 134, 4, 174, 72, 180, 106, 3, 123, 192, 151, 64, 193, 162, 173, 25, 153, 93, 101, 34, 39, 5, 165, 83, 59, 142, 30, 62, 75, 18, 79, 102, 11, 182, 116, 161, 132, 160, 150, 26, 81, 197, 41, 154, 181, 125, 0], Robot Group: [[93, 112, 53, 28, 208, 144, 122, 45, 74, 78, 94, 101], [173, 130, 14, 92, 204, 114, 111, 84, 205, 7, 27, 25], [97, 129, 183, 143, 50, 190, 56, 98, 121, 35, 32, 187], [80, 110, 147, 139, 133, 77, 202, 188, 87, 99, 146, 8], [209, 137, 124, 17, 127, 20, 175, 58, 131, 88, 44, 51], [149, 108, 46, 70, 140, 40, 90, 38, 49, 57, 191, 119], [181, 21, 95, 194, 105, 136, 10, 167, 13, 29, 201, 125], [102, 100, 207, 65, 199, 63, 96, 15, 163, 156, 179, 11], [3, 118, 55, 12, 31, 16, 82, 24, 138, 152, 148, 123]]\n",
      "Vehicle 0: 55378 m, 360.068 min, including 64.69 mins waiting time.\n",
      "Total distance of all routes: : 55378 m\n",
      "Maximum travel time: 360.068 min\n",
      "VRP-RD\n",
      "Routes: [[0, 189, 158, 195, 178, 203, 115, 76, 9, 73, 169, 168, 52, 117, 2, 177, 97, 129, 183, 143, 50, 190, 56, 98, 121, 35, 32, 187, 164, 54, 36, 6, 157, 85, 126, 107, 200, 104, 196, 159, 43, 19, 184, 209, 137, 124, 17, 127, 20, 175, 58, 131, 88, 44, 51, 135, 47, 186, 69, 42, 103, 155, 120, 176, 113, 89, 166, 171, 206, 60, 198, 149, 108, 46, 70, 140, 40, 90, 38, 49, 57, 191, 119, 170, 33, 80, 110, 147, 139, 133, 77, 202, 188, 87, 99, 146, 8, 141, 91, 66, 67, 23, 68, 86, 1, 37, 109, 61, 145, 48, 71, 185, 128, 172, 22, 134, 4, 174, 72, 180, 106, 3, 118, 55, 12, 31, 16, 82, 24, 138, 152, 148, 123, 192, 151, 64, 193, 162, 173, 130, 14, 92, 204, 114, 111, 84, 205, 7, 27, 25, 153, 93, 112, 53, 28, 208, 144, 122, 45, 74, 78, 94, 101, 34, 39, 5, 165, 83, 59, 142, 30, 62, 75, 18, 79, 102, 100, 207, 65, 199, 63, 96, 15, 163, 156, 179, 11, 182, 116, 161, 132, 160, 150, 26, 81, 197, 41, 154, 181, 21, 95, 194, 105, 136, 10, 167, 13, 29, 201, 125, 0]], Length: 211\n",
      "Robot Routes: [[[93, 112, 53, 28, 208, 144, 122, 45, 74, 78, 94, 101], [173, 130, 14, 92, 204, 114, 111, 84, 205, 7, 27, 25], [97, 129, 183, 143, 50, 190, 56, 98, 121, 35, 32, 187], [80, 110, 147, 139, 133, 77, 202, 188, 87, 99, 146, 8], [209, 137, 124, 17, 127, 20, 175, 58, 131, 88, 44, 51], [149, 108, 46, 70, 140, 40, 90, 38, 49, 57, 191, 119], [181, 21, 95, 194, 105, 136, 10, 167, 13, 29, 201, 125], [102, 100, 207, 65, 199, 63, 96, 15, 163, 156, 179, 11], [3, 118, 55, 12, 31, 16, 82, 24, 138, 152, 148, 123]]]\n",
      "Route: [0, 189, 158, 195, 178, 203, 115, 76, 9, 73, 169, 168, 52, 117, 2, 177, 97, 187, 164, 54, 36, 6, 157, 85, 126, 107, 200, 104, 196, 159, 43, 19, 184, 209, 51, 135, 47, 186, 69, 42, 103, 155, 120, 176, 113, 89, 166, 171, 206, 60, 198, 149, 119, 170, 33, 80, 8, 141, 91, 66, 67, 23, 68, 86, 1, 37, 109, 61, 145, 48, 71, 185, 128, 172, 22, 134, 4, 174, 72, 180, 106, 3, 123, 192, 151, 64, 193, 162, 173, 25, 153, 93, 101, 34, 39, 5, 165, 83, 59, 142, 30, 62, 75, 18, 79, 102, 11, 182, 116, 161, 132, 160, 150, 26, 81, 197, 41, 154, 181, 125, 0], Robot Group: [[93, 112, 53, 28, 208, 144, 122, 45, 74, 78, 94, 101], [173, 130, 14, 92, 204, 114, 111, 84, 205, 7, 27, 25], [97, 129, 183, 143, 50, 190, 56, 98, 121, 35, 32, 187], [80, 110, 147, 139, 133, 77, 202, 188, 87, 99, 146, 8], [209, 137, 124, 17, 127, 20, 175, 58, 131, 88, 44, 51], [149, 108, 46, 70, 140, 40, 90, 38, 49, 57, 191, 119], [181, 21, 95, 194, 105, 136, 10, 167, 13, 29, 201, 125], [102, 100, 207, 65, 199, 63, 96, 15, 163, 156, 179, 11], [3, 118, 55, 12, 31, 16, 82, 24, 138, 152, 148, 123]]\n",
      "Vehicle 0: 53392 m, 356.777 min, including 79.385 mins waiting time.\n",
      "Total distance of all routes: : 53392 m\n",
      "Maximum travel time: 356.777 min\n",
      "Trial 23...\n",
      "VRP\n",
      "Routes: [[0, 18, 142, 161, 25, 138, 55, 87, 133, 201, 97, 143, 103, 110, 206, 100, 66, 185, 51, 24, 99, 127, 96, 46, 79, 72, 16, 23, 111, 91, 131, 149, 4, 150, 188, 57, 115, 153, 183, 159, 124, 166, 63, 60, 85, 170, 34, 69, 39, 126, 74, 73, 7, 144, 197, 32, 93, 195, 179, 22, 177, 56, 86, 11, 67, 49, 163, 77, 44, 198, 17, 151, 12, 68, 158, 88, 191, 199, 31, 155, 20, 178, 120, 164, 37, 15, 118, 9, 29, 98, 35, 116, 84, 107, 114, 132, 169, 180, 45, 203, 19, 95, 208, 128, 27, 193, 53, 21, 175, 106, 148, 94, 186, 3, 137, 64, 2, 154, 141, 192, 89, 52, 172, 28, 145, 122, 190, 117, 13, 75, 209, 146, 6, 83, 202, 30, 92, 65, 109, 61, 134, 121, 5, 41, 189, 26, 76, 165, 168, 71, 38, 196, 123, 62, 129, 156, 14, 58, 33, 200, 171, 184, 130, 59, 135, 101, 36, 80, 78, 152, 125, 50, 112, 147, 40, 160, 173, 136, 47, 42, 48, 187, 113, 167, 139, 140, 204, 102, 119, 81, 194, 176, 10, 1, 104, 157, 205, 182, 82, 108, 54, 181, 207, 174, 105, 70, 43, 8, 162, 90, 0]], Length: 211\n",
      "Vehicle 0: 68668 m, 488.668 min, including 0 mins waiting time.\n",
      "Total distance of all routes: : 68668 m\n",
      "Maximum travel time: 488.668 min\n",
      "VRP-D\n",
      "Routes: [[0, 18, 142, 161, 25, 138, 55, 87, 133, 201, 97, 143, 103, 110, 206, 100, 66, 185, 51, 24, 99, 127, 96, 46, 79, 72, 16, 23, 111, 91, 131, 149, 4, 150, 188, 57, 115, 153, 183, 159, 124, 166, 63, 60, 85, 170, 34, 69, 39, 126, 74, 73, 7, 144, 197, 32, 93, 195, 179, 22, 177, 56, 86, 11, 67, 49, 163, 77, 44, 198, 17, 151, 12, 68, 158, 88, 191, 199, 31, 155, 20, 178, 120, 164, 37, 15, 118, 9, 29, 98, 35, 116, 84, 107, 114, 132, 169, 180, 45, 203, 19, 95, 208, 128, 27, 193, 53, 21, 175, 106, 148, 94, 186, 3, 137, 64, 2, 154, 141, 192, 89, 52, 172, 28, 145, 122, 190, 117, 13, 75, 209, 146, 6, 83, 202, 30, 92, 65, 109, 61, 134, 121, 5, 41, 189, 26, 76, 165, 168, 71, 38, 196, 123, 62, 129, 156, 14, 58, 33, 200, 171, 184, 130, 59, 135, 101, 36, 80, 78, 152, 125, 50, 112, 147, 40, 160, 173, 136, 47, 42, 48, 187, 113, 167, 139, 140, 204, 102, 119, 81, 194, 176, 10, 1, 104, 157, 205, 182, 82, 108, 54, 181, 207, 174, 105, 70, 43, 8, 162, 90, 0]], Length: 211\n",
      "Vehicle 0: 65490 m, 465.257 min, including 13.767 mins waiting time.\n",
      "Total distance of all routes: : 65490 m\n",
      "Maximum travel time: 465.257 min\n",
      "VRP-R\n",
      "Routes: [[0, 18, 142, 161, 25, 138, 55, 87, 133, 201, 97, 143, 103, 110, 206, 100, 66, 185, 51, 24, 99, 127, 96, 46, 79, 72, 16, 23, 111, 91, 131, 149, 4, 150, 188, 57, 115, 153, 183, 159, 124, 166, 63, 60, 85, 170, 34, 69, 39, 126, 74, 73, 7, 144, 197, 32, 93, 195, 179, 22, 177, 56, 86, 11, 67, 49, 163, 77, 44, 198, 17, 151, 12, 68, 158, 88, 191, 199, 31, 155, 20, 178, 120, 164, 37, 15, 118, 9, 29, 98, 35, 116, 84, 107, 114, 132, 169, 180, 45, 203, 19, 95, 208, 128, 27, 193, 53, 21, 175, 106, 148, 94, 186, 3, 137, 64, 2, 154, 141, 192, 89, 52, 172, 28, 145, 122, 190, 117, 13, 75, 209, 146, 6, 83, 202, 30, 92, 65, 109, 61, 134, 121, 5, 41, 189, 26, 76, 165, 168, 71, 38, 196, 123, 62, 129, 156, 14, 58, 33, 200, 171, 184, 130, 59, 135, 101, 36, 80, 78, 152, 125, 50, 112, 147, 40, 160, 173, 136, 47, 42, 48, 187, 113, 167, 139, 140, 204, 102, 119, 81, 194, 176, 10, 1, 104, 157, 205, 182, 82, 108, 54, 181, 207, 174, 105, 70, 43, 8, 162, 90, 0]], Length: 211\n",
      "Robot Routes: [[[33, 200, 171, 184, 130, 59, 135, 101, 36, 80, 78, 152], [48, 187, 113, 167, 139, 140, 204, 102, 119, 81, 194, 176], [189, 26, 76, 165, 168, 71, 38, 196, 123, 62, 129, 156], [132, 169, 180, 45, 203, 19, 95, 208, 128, 27, 193, 53], [63, 60, 85, 170, 34, 69, 39, 126, 74, 73, 7, 144], [31, 155, 20, 178, 120, 164, 37, 15, 118, 9, 29, 98]]]\n",
      "Route: [0, 18, 142, 161, 25, 138, 55, 87, 133, 201, 97, 143, 103, 110, 206, 100, 66, 185, 51, 24, 99, 127, 96, 46, 79, 72, 16, 23, 111, 91, 131, 149, 4, 150, 188, 57, 115, 153, 183, 159, 124, 166, 63, 144, 197, 32, 93, 195, 179, 22, 177, 56, 86, 11, 67, 49, 163, 77, 44, 198, 17, 151, 12, 68, 158, 88, 191, 199, 31, 98, 35, 116, 84, 107, 114, 132, 53, 21, 175, 106, 148, 94, 186, 3, 137, 64, 2, 154, 141, 192, 89, 52, 172, 28, 145, 122, 190, 117, 13, 75, 209, 146, 6, 83, 202, 30, 92, 65, 109, 61, 134, 121, 5, 41, 189, 156, 14, 58, 33, 152, 125, 50, 112, 147, 40, 160, 173, 136, 47, 42, 48, 176, 10, 1, 104, 157, 205, 182, 82, 108, 54, 181, 207, 174, 105, 70, 43, 8, 162, 90, 0], Robot Group: [[33, 200, 171, 184, 130, 59, 135, 101, 36, 80, 78, 152], [48, 187, 113, 167, 139, 140, 204, 102, 119, 81, 194, 176], [189, 26, 76, 165, 168, 71, 38, 196, 123, 62, 129, 156], [132, 169, 180, 45, 203, 19, 95, 208, 128, 27, 193, 53], [63, 60, 85, 170, 34, 69, 39, 126, 74, 73, 7, 144], [31, 155, 20, 178, 120, 164, 37, 15, 118, 9, 29, 98]]\n",
      "Vehicle 0: 63625 m, 381.591 min, including 17.966 mins waiting time.\n",
      "Total distance of all routes: : 63625 m\n",
      "Maximum travel time: 381.591 min\n",
      "VRP-RD\n",
      "Routes: [[0, 18, 142, 161, 25, 138, 55, 87, 133, 201, 97, 143, 103, 110, 206, 100, 66, 185, 51, 24, 99, 127, 96, 46, 79, 72, 16, 23, 111, 91, 131, 149, 4, 150, 188, 57, 115, 153, 183, 159, 124, 166, 63, 60, 85, 170, 34, 69, 39, 126, 74, 73, 7, 144, 197, 32, 93, 195, 179, 22, 177, 56, 86, 11, 67, 49, 163, 77, 44, 198, 17, 151, 12, 68, 158, 88, 191, 199, 31, 155, 20, 178, 120, 164, 37, 15, 118, 9, 29, 98, 35, 116, 84, 107, 114, 132, 169, 180, 45, 203, 19, 95, 208, 128, 27, 193, 53, 21, 175, 106, 148, 94, 186, 3, 137, 64, 2, 154, 141, 192, 89, 52, 172, 28, 145, 122, 190, 117, 13, 75, 209, 146, 6, 83, 202, 30, 92, 65, 109, 61, 134, 121, 5, 41, 189, 26, 76, 165, 168, 71, 38, 196, 123, 62, 129, 156, 14, 58, 33, 200, 171, 184, 130, 59, 135, 101, 36, 80, 78, 152, 125, 50, 112, 147, 40, 160, 173, 136, 47, 42, 48, 187, 113, 167, 139, 140, 204, 102, 119, 81, 194, 176, 10, 1, 104, 157, 205, 182, 82, 108, 54, 181, 207, 174, 105, 70, 43, 8, 162, 90, 0]], Length: 211\n",
      "Robot Routes: [[[33, 200, 171, 184, 130, 59, 135, 101, 36, 80, 78, 152], [48, 187, 113, 167, 139, 140, 204, 102, 119, 81, 194, 176], [189, 26, 76, 165, 168, 71, 38, 196, 123, 62, 129, 156], [132, 169, 180, 45, 203, 19, 95, 208, 128, 27, 193, 53], [63, 60, 85, 170, 34, 69, 39, 126, 74, 73, 7, 144], [31, 155, 20, 178, 120, 164, 37, 15, 118, 9, 29, 98]]]\n",
      "Route: [0, 18, 142, 161, 25, 138, 55, 87, 133, 201, 97, 143, 103, 110, 206, 100, 66, 185, 51, 24, 99, 127, 96, 46, 79, 72, 16, 23, 111, 91, 131, 149, 4, 150, 188, 57, 115, 153, 183, 159, 124, 166, 63, 144, 197, 32, 93, 195, 179, 22, 177, 56, 86, 11, 67, 49, 163, 77, 44, 198, 17, 151, 12, 68, 158, 88, 191, 199, 31, 98, 35, 116, 84, 107, 114, 132, 53, 21, 175, 106, 148, 94, 186, 3, 137, 64, 2, 154, 141, 192, 89, 52, 172, 28, 145, 122, 190, 117, 13, 75, 209, 146, 6, 83, 202, 30, 92, 65, 109, 61, 134, 121, 5, 41, 189, 156, 14, 58, 33, 152, 125, 50, 112, 147, 40, 160, 173, 136, 47, 42, 48, 176, 10, 1, 104, 157, 205, 182, 82, 108, 54, 181, 207, 174, 105, 70, 43, 8, 162, 90, 0], Robot Group: [[33, 200, 171, 184, 130, 59, 135, 101, 36, 80, 78, 152], [48, 187, 113, 167, 139, 140, 204, 102, 119, 81, 194, 176], [189, 26, 76, 165, 168, 71, 38, 196, 123, 62, 129, 156], [132, 169, 180, 45, 203, 19, 95, 208, 128, 27, 193, 53], [63, 60, 85, 170, 34, 69, 39, 126, 74, 73, 7, 144], [31, 155, 20, 178, 120, 164, 37, 15, 118, 9, 29, 98]]\n",
      "Vehicle 0: 60743 m, 366.92 min, including 32.177 mins waiting time.\n",
      "Total distance of all routes: : 60743 m\n",
      "Maximum travel time: 366.92 min\n",
      "Trial 24...\n",
      "VRP\n",
      "Routes: [[0, 69, 170, 72, 201, 167, 37, 174, 50, 57, 206, 63, 27, 100, 112, 15, 106, 68, 46, 168, 121, 166, 196, 179, 137, 87, 41, 58, 35, 131, 103, 184, 148, 190, 143, 74, 56, 125, 47, 207, 209, 22, 95, 176, 77, 191, 12, 3, 158, 208, 76, 133, 11, 128, 52, 199, 130, 88, 178, 39, 192, 23, 149, 48, 147, 136, 185, 104, 145, 30, 51, 163, 120, 154, 62, 107, 7, 113, 32, 83, 151, 98, 195, 59, 160, 80, 44, 115, 164, 177, 161, 187, 101, 102, 89, 135, 84, 204, 142, 19, 175, 127, 64, 171, 116, 9, 91, 183, 14, 81, 38, 8, 16, 134, 54, 182, 21, 92, 169, 25, 202, 43, 5, 189, 150, 85, 26, 123, 13, 124, 118, 114, 180, 144, 24, 139, 36, 86, 17, 188, 117, 198, 94, 67, 132, 194, 78, 66, 93, 153, 193, 138, 60, 203, 126, 6, 108, 33, 157, 40, 90, 18, 4, 156, 71, 146, 109, 172, 99, 10, 111, 49, 45, 159, 96, 165, 141, 55, 122, 73, 186, 1, 29, 53, 28, 205, 79, 200, 119, 155, 42, 162, 110, 197, 97, 181, 129, 34, 105, 82, 152, 20, 173, 140, 61, 65, 31, 75, 2, 70, 0]], Length: 211\n",
      "Vehicle 0: 68966 m, 488.966 min, including 0 mins waiting time.\n",
      "Total distance of all routes: : 68966 m\n",
      "Maximum travel time: 488.966 min\n",
      "VRP-D\n",
      "Routes: [[0, 69, 170, 72, 201, 167, 37, 174, 50, 57, 206, 63, 27, 100, 112, 15, 106, 68, 46, 168, 121, 166, 196, 179, 137, 87, 41, 58, 35, 131, 103, 184, 148, 190, 143, 74, 56, 125, 47, 207, 209, 22, 95, 176, 77, 191, 12, 3, 158, 208, 76, 133, 11, 128, 52, 199, 130, 88, 178, 39, 192, 23, 149, 48, 147, 136, 185, 104, 145, 30, 51, 163, 120, 154, 62, 107, 7, 113, 32, 83, 151, 98, 195, 59, 160, 80, 44, 115, 164, 177, 161, 187, 101, 102, 89, 135, 84, 204, 142, 19, 175, 127, 64, 171, 116, 9, 91, 183, 14, 81, 38, 8, 16, 134, 54, 182, 21, 92, 169, 25, 202, 43, 5, 189, 150, 85, 26, 123, 13, 124, 118, 114, 180, 144, 24, 139, 36, 86, 17, 188, 117, 198, 94, 67, 132, 194, 78, 66, 93, 153, 193, 138, 60, 203, 126, 6, 108, 33, 157, 40, 90, 18, 4, 156, 71, 146, 109, 172, 99, 10, 111, 49, 45, 159, 96, 165, 141, 55, 122, 73, 186, 1, 29, 53, 28, 205, 79, 200, 119, 155, 42, 162, 110, 197, 97, 181, 129, 34, 105, 82, 152, 20, 173, 140, 61, 65, 31, 75, 2, 70, 0]], Length: 211\n",
      "Vehicle 0: 64454 m, 465.194 min, including 14.74 mins waiting time.\n",
      "Total distance of all routes: : 64454 m\n",
      "Maximum travel time: 465.194 min\n",
      "VRP-R\n",
      "Routes: [[0, 69, 170, 72, 201, 167, 37, 174, 50, 57, 206, 63, 27, 100, 112, 15, 106, 68, 46, 168, 121, 166, 196, 179, 137, 87, 41, 58, 35, 131, 103, 184, 148, 190, 143, 74, 56, 125, 47, 207, 209, 22, 95, 176, 77, 191, 12, 3, 158, 208, 76, 133, 11, 128, 52, 199, 130, 88, 178, 39, 192, 23, 149, 48, 147, 136, 185, 104, 145, 30, 51, 163, 120, 154, 62, 107, 7, 113, 32, 83, 151, 98, 195, 59, 160, 80, 44, 115, 164, 177, 161, 187, 101, 102, 89, 135, 84, 204, 142, 19, 175, 127, 64, 171, 116, 9, 91, 183, 14, 81, 38, 8, 16, 134, 54, 182, 21, 92, 169, 25, 202, 43, 5, 189, 150, 85, 26, 123, 13, 124, 118, 114, 180, 144, 24, 139, 36, 86, 17, 188, 117, 198, 94, 67, 132, 194, 78, 66, 93, 153, 193, 138, 60, 203, 126, 6, 108, 33, 157, 40, 90, 18, 4, 156, 71, 146, 109, 172, 99, 10, 111, 49, 45, 159, 96, 165, 141, 55, 122, 73, 186, 1, 29, 53, 28, 205, 79, 200, 119, 155, 42, 162, 110, 197, 97, 181, 129, 34, 105, 82, 152, 20, 173, 140, 61, 65, 31, 75, 2, 70, 0]], Length: 211\n",
      "Robot Routes: [[[96, 165, 141, 55, 122, 73, 186, 1, 29, 53, 28, 205], [82, 152, 20, 173, 140, 61, 65, 31, 75, 2, 70, 0], [38, 8, 16, 134, 54, 182, 21, 92, 169, 25, 202, 43], [199, 130, 88, 178, 39, 192, 23, 149, 48, 147, 136, 185], [13, 124, 118, 114, 180, 144, 24, 139, 36, 86, 17, 188], [157, 40, 90, 18, 4, 156, 71, 146, 109, 172, 99, 10], [151, 98, 195, 59, 160, 80, 44, 115, 164, 177, 161, 187]]]\n",
      "Route: [0, 69, 170, 72, 201, 167, 37, 174, 50, 57, 206, 63, 27, 100, 112, 15, 106, 68, 46, 168, 121, 166, 196, 179, 137, 87, 41, 58, 35, 131, 103, 184, 148, 190, 143, 74, 56, 125, 47, 207, 209, 22, 95, 176, 77, 191, 12, 3, 158, 208, 76, 133, 11, 128, 52, 199, 185, 104, 145, 30, 51, 163, 120, 154, 62, 107, 7, 113, 32, 83, 151, 187, 101, 102, 89, 135, 84, 204, 142, 19, 175, 127, 64, 171, 116, 9, 91, 183, 14, 81, 38, 43, 5, 189, 150, 85, 26, 123, 13, 188, 117, 198, 94, 67, 132, 194, 78, 66, 93, 153, 193, 138, 60, 203, 126, 6, 108, 33, 157, 10, 111, 49, 45, 159, 96, 205, 79, 200, 119, 155, 42, 162, 110, 197, 97, 181, 129, 34, 105, 82, 0], Robot Group: [[96, 165, 141, 55, 122, 73, 186, 1, 29, 53, 28, 205], [82, 152, 20, 173, 140, 61, 65, 31, 75, 2, 70, 0], [38, 8, 16, 134, 54, 182, 21, 92, 169, 25, 202, 43], [199, 130, 88, 178, 39, 192, 23, 149, 48, 147, 136, 185], [13, 124, 118, 114, 180, 144, 24, 139, 36, 86, 17, 188], [157, 40, 90, 18, 4, 156, 71, 146, 109, 172, 99, 10], [151, 98, 195, 59, 160, 80, 44, 115, 164, 177, 161, 187]]\n",
      "Vehicle 0: 60969 m, 394.108 min, including 51.139 mins waiting time.\n",
      "Total distance of all routes: : 60969 m\n",
      "Maximum travel time: 394.108 min\n",
      "VRP-RD\n",
      "Routes: [[0, 69, 170, 72, 201, 167, 37, 174, 50, 57, 206, 63, 27, 100, 112, 15, 106, 68, 46, 168, 121, 166, 196, 179, 137, 87, 41, 58, 35, 131, 103, 184, 148, 190, 143, 74, 56, 125, 47, 207, 209, 22, 95, 176, 77, 191, 12, 3, 158, 208, 76, 133, 11, 128, 52, 199, 130, 88, 178, 39, 192, 23, 149, 48, 147, 136, 185, 104, 145, 30, 51, 163, 120, 154, 62, 107, 7, 113, 32, 83, 151, 98, 195, 59, 160, 80, 44, 115, 164, 177, 161, 187, 101, 102, 89, 135, 84, 204, 142, 19, 175, 127, 64, 171, 116, 9, 91, 183, 14, 81, 38, 8, 16, 134, 54, 182, 21, 92, 169, 25, 202, 43, 5, 189, 150, 85, 26, 123, 13, 124, 118, 114, 180, 144, 24, 139, 36, 86, 17, 188, 117, 198, 94, 67, 132, 194, 78, 66, 93, 153, 193, 138, 60, 203, 126, 6, 108, 33, 157, 40, 90, 18, 4, 156, 71, 146, 109, 172, 99, 10, 111, 49, 45, 159, 96, 165, 141, 55, 122, 73, 186, 1, 29, 53, 28, 205, 79, 200, 119, 155, 42, 162, 110, 197, 97, 181, 129, 34, 105, 82, 152, 20, 173, 140, 61, 65, 31, 75, 2, 70, 0]], Length: 211\n",
      "Robot Routes: [[[96, 165, 141, 55, 122, 73, 186, 1, 29, 53, 28, 205], [82, 152, 20, 173, 140, 61, 65, 31, 75, 2, 70, 0], [38, 8, 16, 134, 54, 182, 21, 92, 169, 25, 202, 43], [199, 130, 88, 178, 39, 192, 23, 149, 48, 147, 136, 185], [13, 124, 118, 114, 180, 144, 24, 139, 36, 86, 17, 188], [157, 40, 90, 18, 4, 156, 71, 146, 109, 172, 99, 10], [151, 98, 195, 59, 160, 80, 44, 115, 164, 177, 161, 187]]]\n",
      "Route: [0, 69, 170, 72, 201, 167, 37, 174, 50, 57, 206, 63, 27, 100, 112, 15, 106, 68, 46, 168, 121, 166, 196, 179, 137, 87, 41, 58, 35, 131, 103, 184, 148, 190, 143, 74, 56, 125, 47, 207, 209, 22, 95, 176, 77, 191, 12, 3, 158, 208, 76, 133, 11, 128, 52, 199, 185, 104, 145, 30, 51, 163, 120, 154, 62, 107, 7, 113, 32, 83, 151, 187, 101, 102, 89, 135, 84, 204, 142, 19, 175, 127, 64, 171, 116, 9, 91, 183, 14, 81, 38, 43, 5, 189, 150, 85, 26, 123, 13, 188, 117, 198, 94, 67, 132, 194, 78, 66, 93, 153, 193, 138, 60, 203, 126, 6, 108, 33, 157, 10, 111, 49, 45, 159, 96, 205, 79, 200, 119, 155, 42, 162, 110, 197, 97, 181, 129, 34, 105, 82, 0], Robot Group: [[96, 165, 141, 55, 122, 73, 186, 1, 29, 53, 28, 205], [82, 152, 20, 173, 140, 61, 65, 31, 75, 2, 70, 0], [38, 8, 16, 134, 54, 182, 21, 92, 169, 25, 202, 43], [199, 130, 88, 178, 39, 192, 23, 149, 48, 147, 136, 185], [13, 124, 118, 114, 180, 144, 24, 139, 36, 86, 17, 188], [157, 40, 90, 18, 4, 156, 71, 146, 109, 172, 99, 10], [151, 98, 195, 59, 160, 80, 44, 115, 164, 177, 161, 187]]\n",
      "Vehicle 0: 57716 m, 382.737 min, including 65.021 mins waiting time.\n",
      "Total distance of all routes: : 57716 m\n",
      "Maximum travel time: 382.737 min\n",
      "Trial 25...\n",
      "VRP\n",
      "Routes: [[0, 196, 3, 63, 193, 44, 164, 129, 116, 108, 172, 89, 166, 97, 104, 57, 14, 182, 128, 25, 201, 83, 106, 26, 137, 55, 148, 174, 205, 27, 73, 74, 203, 62, 93, 208, 161, 43, 115, 191, 144, 45, 189, 179, 117, 202, 7, 178, 149, 165, 84, 85, 100, 98, 28, 82, 8, 32, 46, 159, 61, 121, 86, 41, 58, 130, 5, 127, 146, 152, 31, 125, 38, 177, 77, 30, 168, 111, 183, 185, 162, 76, 110, 67, 12, 198, 49, 17, 119, 195, 200, 33, 167, 42, 4, 171, 120, 36, 54, 114, 2, 21, 35, 75, 190, 133, 173, 112, 199, 163, 176, 64, 132, 143, 90, 184, 16, 52, 66, 134, 102, 126, 187, 99, 78, 40, 141, 206, 24, 22, 158, 105, 10, 37, 80, 136, 138, 91, 94, 151, 207, 131, 140, 87, 197, 13, 156, 92, 18, 68, 79, 160, 70, 139, 19, 71, 122, 169, 1, 15, 186, 107, 50, 69, 23, 34, 51, 6, 175, 101, 95, 180, 39, 103, 53, 124, 154, 150, 188, 60, 109, 142, 48, 96, 155, 29, 153, 113, 65, 56, 181, 204, 9, 192, 47, 72, 88, 11, 81, 59, 194, 118, 170, 147, 145, 209, 135, 123, 157, 20, 0]], Length: 211\n",
      "Vehicle 0: 72364 m, 492.364 min, including 0 mins waiting time.\n",
      "Total distance of all routes: : 72364 m\n",
      "Maximum travel time: 492.364 min\n",
      "VRP-D\n",
      "Routes: [[0, 196, 3, 63, 193, 44, 164, 129, 116, 108, 172, 89, 166, 97, 104, 57, 14, 182, 128, 25, 201, 83, 106, 26, 137, 55, 148, 174, 205, 27, 73, 74, 203, 62, 93, 208, 161, 43, 115, 191, 144, 45, 189, 179, 117, 202, 7, 178, 149, 165, 84, 85, 100, 98, 28, 82, 8, 32, 46, 159, 61, 121, 86, 41, 58, 130, 5, 127, 146, 152, 31, 125, 38, 177, 77, 30, 168, 111, 183, 185, 162, 76, 110, 67, 12, 198, 49, 17, 119, 195, 200, 33, 167, 42, 4, 171, 120, 36, 54, 114, 2, 21, 35, 75, 190, 133, 173, 112, 199, 163, 176, 64, 132, 143, 90, 184, 16, 52, 66, 134, 102, 126, 187, 99, 78, 40, 141, 206, 24, 22, 158, 105, 10, 37, 80, 136, 138, 91, 94, 151, 207, 131, 140, 87, 197, 13, 156, 92, 18, 68, 79, 160, 70, 139, 19, 71, 122, 169, 1, 15, 186, 107, 50, 69, 23, 34, 51, 6, 175, 101, 95, 180, 39, 103, 53, 124, 154, 150, 188, 60, 109, 142, 48, 96, 155, 29, 153, 113, 65, 56, 181, 204, 9, 192, 47, 72, 88, 11, 81, 59, 194, 118, 170, 147, 145, 209, 135, 123, 157, 20, 0]], Length: 211\n",
      "Vehicle 0: 69661 m, 470.25 min, including 12.589 mins waiting time.\n",
      "Total distance of all routes: : 69661 m\n",
      "Maximum travel time: 470.25 min\n",
      "VRP-R\n",
      "Routes: [[0, 196, 3, 63, 193, 44, 164, 129, 116, 108, 172, 89, 166, 97, 104, 57, 14, 182, 128, 25, 201, 83, 106, 26, 137, 55, 148, 174, 205, 27, 73, 74, 203, 62, 93, 208, 161, 43, 115, 191, 144, 45, 189, 179, 117, 202, 7, 178, 149, 165, 84, 85, 100, 98, 28, 82, 8, 32, 46, 159, 61, 121, 86, 41, 58, 130, 5, 127, 146, 152, 31, 125, 38, 177, 77, 30, 168, 111, 183, 185, 162, 76, 110, 67, 12, 198, 49, 17, 119, 195, 200, 33, 167, 42, 4, 171, 120, 36, 54, 114, 2, 21, 35, 75, 190, 133, 173, 112, 199, 163, 176, 64, 132, 143, 90, 184, 16, 52, 66, 134, 102, 126, 187, 99, 78, 40, 141, 206, 24, 22, 158, 105, 10, 37, 80, 136, 138, 91, 94, 151, 207, 131, 140, 87, 197, 13, 156, 92, 18, 68, 79, 160, 70, 139, 19, 71, 122, 169, 1, 15, 186, 107, 50, 69, 23, 34, 51, 6, 175, 101, 95, 180, 39, 103, 53, 124, 154, 150, 188, 60, 109, 142, 48, 96, 155, 29, 153, 113, 65, 56, 181, 204, 9, 192, 47, 72, 88, 11, 81, 59, 194, 118, 170, 147, 145, 209, 135, 123, 157, 20, 0]], Length: 211\n",
      "Robot Routes: [[[163, 176, 64, 132, 143, 90, 184, 16, 52, 66, 134, 102], [129, 116, 108, 172, 89, 166, 97, 104, 57, 14, 182, 128], [106, 26, 137, 55, 148, 174, 205, 27, 73, 74, 203, 62], [183, 185, 162, 76, 110, 67, 12, 198, 49, 17, 119, 195], [160, 70, 139, 19, 71, 122, 169, 1, 15, 186, 107, 50], [69, 23, 34, 51, 6, 175, 101, 95, 180, 39, 103, 53], [81, 59, 194, 118, 170, 147, 145, 209, 135, 123, 157, 20], [191, 144, 45, 189, 179, 117, 202, 7, 178, 149, 165, 84], [94, 151, 207, 131, 140, 87, 197, 13, 156, 92, 18, 68]]]\n",
      "Route: [0, 196, 3, 63, 193, 44, 164, 129, 128, 25, 201, 83, 106, 62, 93, 208, 161, 43, 115, 191, 84, 85, 100, 98, 28, 82, 8, 32, 46, 159, 61, 121, 86, 41, 58, 130, 5, 127, 146, 152, 31, 125, 38, 177, 77, 30, 168, 111, 183, 195, 200, 33, 167, 42, 4, 171, 120, 36, 54, 114, 2, 21, 35, 75, 190, 133, 173, 112, 199, 163, 102, 126, 187, 99, 78, 40, 141, 206, 24, 22, 158, 105, 10, 37, 80, 136, 138, 91, 94, 68, 79, 160, 50, 69, 53, 124, 154, 150, 188, 60, 109, 142, 48, 96, 155, 29, 153, 113, 65, 56, 181, 204, 9, 192, 47, 72, 88, 11, 81, 20, 0], Robot Group: [[163, 176, 64, 132, 143, 90, 184, 16, 52, 66, 134, 102], [129, 116, 108, 172, 89, 166, 97, 104, 57, 14, 182, 128], [106, 26, 137, 55, 148, 174, 205, 27, 73, 74, 203, 62], [183, 185, 162, 76, 110, 67, 12, 198, 49, 17, 119, 195], [160, 70, 139, 19, 71, 122, 169, 1, 15, 186, 107, 50], [69, 23, 34, 51, 6, 175, 101, 95, 180, 39, 103, 53], [81, 59, 194, 118, 170, 147, 145, 209, 135, 123, 157, 20], [191, 144, 45, 189, 179, 117, 202, 7, 178, 149, 165, 84], [94, 151, 207, 131, 140, 87, 197, 13, 156, 92, 18, 68]]\n",
      "Vehicle 0: 57796 m, 351.803 min, including 54.007 mins waiting time.\n",
      "Total distance of all routes: : 57796 m\n",
      "Maximum travel time: 351.803 min\n",
      "VRP-RD\n",
      "Routes: [[0, 196, 3, 63, 193, 44, 164, 129, 116, 108, 172, 89, 166, 97, 104, 57, 14, 182, 128, 25, 201, 83, 106, 26, 137, 55, 148, 174, 205, 27, 73, 74, 203, 62, 93, 208, 161, 43, 115, 191, 144, 45, 189, 179, 117, 202, 7, 178, 149, 165, 84, 85, 100, 98, 28, 82, 8, 32, 46, 159, 61, 121, 86, 41, 58, 130, 5, 127, 146, 152, 31, 125, 38, 177, 77, 30, 168, 111, 183, 185, 162, 76, 110, 67, 12, 198, 49, 17, 119, 195, 200, 33, 167, 42, 4, 171, 120, 36, 54, 114, 2, 21, 35, 75, 190, 133, 173, 112, 199, 163, 176, 64, 132, 143, 90, 184, 16, 52, 66, 134, 102, 126, 187, 99, 78, 40, 141, 206, 24, 22, 158, 105, 10, 37, 80, 136, 138, 91, 94, 151, 207, 131, 140, 87, 197, 13, 156, 92, 18, 68, 79, 160, 70, 139, 19, 71, 122, 169, 1, 15, 186, 107, 50, 69, 23, 34, 51, 6, 175, 101, 95, 180, 39, 103, 53, 124, 154, 150, 188, 60, 109, 142, 48, 96, 155, 29, 153, 113, 65, 56, 181, 204, 9, 192, 47, 72, 88, 11, 81, 59, 194, 118, 170, 147, 145, 209, 135, 123, 157, 20, 0]], Length: 211\n",
      "Robot Routes: [[[163, 176, 64, 132, 143, 90, 184, 16, 52, 66, 134, 102], [129, 116, 108, 172, 89, 166, 97, 104, 57, 14, 182, 128], [106, 26, 137, 55, 148, 174, 205, 27, 73, 74, 203, 62], [183, 185, 162, 76, 110, 67, 12, 198, 49, 17, 119, 195], [160, 70, 139, 19, 71, 122, 169, 1, 15, 186, 107, 50], [69, 23, 34, 51, 6, 175, 101, 95, 180, 39, 103, 53], [81, 59, 194, 118, 170, 147, 145, 209, 135, 123, 157, 20], [191, 144, 45, 189, 179, 117, 202, 7, 178, 149, 165, 84], [94, 151, 207, 131, 140, 87, 197, 13, 156, 92, 18, 68]]]\n",
      "Route: [0, 196, 3, 63, 193, 44, 164, 129, 128, 25, 201, 83, 106, 62, 93, 208, 161, 43, 115, 191, 84, 85, 100, 98, 28, 82, 8, 32, 46, 159, 61, 121, 86, 41, 58, 130, 5, 127, 146, 152, 31, 125, 38, 177, 77, 30, 168, 111, 183, 195, 200, 33, 167, 42, 4, 171, 120, 36, 54, 114, 2, 21, 35, 75, 190, 133, 173, 112, 199, 163, 102, 126, 187, 99, 78, 40, 141, 206, 24, 22, 158, 105, 10, 37, 80, 136, 138, 91, 94, 68, 79, 160, 50, 69, 53, 124, 154, 150, 188, 60, 109, 142, 48, 96, 155, 29, 153, 113, 65, 56, 181, 204, 9, 192, 47, 72, 88, 11, 81, 20, 0], Robot Group: [[163, 176, 64, 132, 143, 90, 184, 16, 52, 66, 134, 102], [129, 116, 108, 172, 89, 166, 97, 104, 57, 14, 182, 128], [106, 26, 137, 55, 148, 174, 205, 27, 73, 74, 203, 62], [183, 185, 162, 76, 110, 67, 12, 198, 49, 17, 119, 195], [160, 70, 139, 19, 71, 122, 169, 1, 15, 186, 107, 50], [69, 23, 34, 51, 6, 175, 101, 95, 180, 39, 103, 53], [81, 59, 194, 118, 170, 147, 145, 209, 135, 123, 157, 20], [191, 144, 45, 189, 179, 117, 202, 7, 178, 149, 165, 84], [94, 151, 207, 131, 140, 87, 197, 13, 156, 92, 18, 68]]\n",
      "Vehicle 0: 56687 m, 341.483 min, including 62.796 mins waiting time.\n",
      "Total distance of all routes: : 56687 m\n",
      "Maximum travel time: 341.483 min\n",
      "Trial 26...\n",
      "VRP\n",
      "Routes: [[0, 86, 196, 121, 43, 112, 54, 57, 170, 10, 190, 110, 122, 161, 51, 117, 120, 70, 49, 183, 167, 66, 192, 160, 42, 149, 102, 33, 209, 67, 138, 111, 22, 87, 185, 27, 154, 175, 76, 173, 50, 62, 99, 12, 11, 65, 9, 179, 155, 181, 106, 64, 91, 194, 18, 30, 169, 126, 176, 137, 153, 101, 144, 26, 90, 206, 195, 23, 40, 95, 115, 37, 146, 129, 38, 28, 48, 2, 200, 14, 132, 130, 177, 97, 143, 123, 180, 13, 108, 156, 77, 80, 208, 109, 4, 125, 128, 46, 16, 44, 61, 69, 60, 72, 150, 6, 163, 199, 104, 114, 58, 145, 21, 78, 68, 71, 186, 84, 197, 93, 184, 127, 96, 113, 35, 36, 205, 39, 148, 55, 79, 5, 19, 116, 168, 53, 81, 135, 207, 45, 63, 191, 174, 85, 164, 157, 24, 131, 178, 188, 92, 25, 151, 98, 136, 124, 171, 15, 202, 41, 203, 82, 34, 20, 17, 182, 166, 142, 198, 133, 201, 107, 140, 32, 7, 8, 172, 59, 152, 73, 141, 83, 119, 94, 134, 159, 187, 75, 118, 165, 56, 100, 52, 1, 74, 31, 193, 189, 162, 3, 103, 105, 29, 139, 147, 158, 47, 88, 89, 204, 0]], Length: 211\n",
      "Vehicle 0: 71915 m, 491.915 min, including 0 mins waiting time.\n",
      "Total distance of all routes: : 71915 m\n",
      "Maximum travel time: 491.915 min\n",
      "VRP-D\n",
      "Routes: [[0, 86, 196, 121, 43, 112, 54, 57, 170, 10, 190, 110, 122, 161, 51, 117, 120, 70, 49, 183, 167, 66, 192, 160, 42, 149, 102, 33, 209, 67, 138, 111, 22, 87, 185, 27, 154, 175, 76, 173, 50, 62, 99, 12, 11, 65, 9, 179, 155, 181, 106, 64, 91, 194, 18, 30, 169, 126, 176, 137, 153, 101, 144, 26, 90, 206, 195, 23, 40, 95, 115, 37, 146, 129, 38, 28, 48, 2, 200, 14, 132, 130, 177, 97, 143, 123, 180, 13, 108, 156, 77, 80, 208, 109, 4, 125, 128, 46, 16, 44, 61, 69, 60, 72, 150, 6, 163, 199, 104, 114, 58, 145, 21, 78, 68, 71, 186, 84, 197, 93, 184, 127, 96, 113, 35, 36, 205, 39, 148, 55, 79, 5, 19, 116, 168, 53, 81, 135, 207, 45, 63, 191, 174, 85, 164, 157, 24, 131, 178, 188, 92, 25, 151, 98, 136, 124, 171, 15, 202, 41, 203, 82, 34, 20, 17, 182, 166, 142, 198, 133, 201, 107, 140, 32, 7, 8, 172, 59, 152, 73, 141, 83, 119, 94, 134, 159, 187, 75, 118, 165, 56, 100, 52, 1, 74, 31, 193, 189, 162, 3, 103, 105, 29, 139, 147, 158, 47, 88, 89, 204, 0]], Length: 211\n",
      "Vehicle 0: 69543 m, 466.824 min, including 13.281 mins waiting time.\n",
      "Total distance of all routes: : 69543 m\n",
      "Maximum travel time: 466.824 min\n",
      "VRP-R\n",
      "Routes: [[0, 86, 196, 121, 43, 112, 54, 57, 170, 10, 190, 110, 122, 161, 51, 117, 120, 70, 49, 183, 167, 66, 192, 160, 42, 149, 102, 33, 209, 67, 138, 111, 22, 87, 185, 27, 154, 175, 76, 173, 50, 62, 99, 12, 11, 65, 9, 179, 155, 181, 106, 64, 91, 194, 18, 30, 169, 126, 176, 137, 153, 101, 144, 26, 90, 206, 195, 23, 40, 95, 115, 37, 146, 129, 38, 28, 48, 2, 200, 14, 132, 130, 177, 97, 143, 123, 180, 13, 108, 156, 77, 80, 208, 109, 4, 125, 128, 46, 16, 44, 61, 69, 60, 72, 150, 6, 163, 199, 104, 114, 58, 145, 21, 78, 68, 71, 186, 84, 197, 93, 184, 127, 96, 113, 35, 36, 205, 39, 148, 55, 79, 5, 19, 116, 168, 53, 81, 135, 207, 45, 63, 191, 174, 85, 164, 157, 24, 131, 178, 188, 92, 25, 151, 98, 136, 124, 171, 15, 202, 41, 203, 82, 34, 20, 17, 182, 166, 142, 198, 133, 201, 107, 140, 32, 7, 8, 172, 59, 152, 73, 141, 83, 119, 94, 134, 159, 187, 75, 118, 165, 56, 100, 52, 1, 74, 31, 193, 189, 162, 3, 103, 105, 29, 139, 147, 158, 47, 88, 89, 204, 0]], Length: 211\n",
      "Robot Routes: [[[44, 61, 69, 60, 72, 150, 6, 163, 199, 104, 114, 58], [28, 48, 2, 200, 14, 132, 130, 177, 97, 143, 123, 180], [0, 86, 196, 121, 43, 112, 54, 57, 170, 10, 190, 110], [13, 108, 156, 77, 80, 208, 109, 4, 125, 128, 46, 16], [32, 7, 8, 172, 59, 152, 73, 141, 83, 119, 94, 134], [164, 157, 24, 131, 178, 188, 92, 25, 151, 98, 136, 124], [15, 202, 41, 203, 82, 34, 20, 17, 182, 166, 142, 198], [165, 56, 100, 52, 1, 74, 31, 193, 189, 162, 3, 103], [42, 149, 102, 33, 209, 67, 138, 111, 22, 87, 185, 27]]]\n",
      "Route: [0, 110, 122, 161, 51, 117, 120, 70, 49, 183, 167, 66, 192, 160, 42, 27, 154, 175, 76, 173, 50, 62, 99, 12, 11, 65, 9, 179, 155, 181, 106, 64, 91, 194, 18, 30, 169, 126, 176, 137, 153, 101, 144, 26, 90, 206, 195, 23, 40, 95, 115, 37, 146, 129, 38, 28, 180, 13, 16, 44, 58, 145, 21, 78, 68, 71, 186, 84, 197, 93, 184, 127, 96, 113, 35, 36, 205, 39, 148, 55, 79, 5, 19, 116, 168, 53, 81, 135, 207, 45, 63, 191, 174, 85, 164, 124, 171, 15, 198, 133, 201, 107, 140, 32, 134, 159, 187, 75, 118, 165, 103, 105, 29, 139, 147, 158, 47, 88, 89, 204, 0], Robot Group: [[44, 61, 69, 60, 72, 150, 6, 163, 199, 104, 114, 58], [28, 48, 2, 200, 14, 132, 130, 177, 97, 143, 123, 180], [0, 86, 196, 121, 43, 112, 54, 57, 170, 10, 190, 110], [13, 108, 156, 77, 80, 208, 109, 4, 125, 128, 46, 16], [32, 7, 8, 172, 59, 152, 73, 141, 83, 119, 94, 134], [164, 157, 24, 131, 178, 188, 92, 25, 151, 98, 136, 124], [15, 202, 41, 203, 82, 34, 20, 17, 182, 166, 142, 198], [165, 56, 100, 52, 1, 74, 31, 193, 189, 162, 3, 103], [42, 149, 102, 33, 209, 67, 138, 111, 22, 87, 185, 27]]\n",
      "Vehicle 0: 58670 m, 370.928 min, including 72.258 mins waiting time.\n",
      "Total distance of all routes: : 58670 m\n",
      "Maximum travel time: 370.928 min\n",
      "VRP-RD\n",
      "Routes: [[0, 86, 196, 121, 43, 112, 54, 57, 170, 10, 190, 110, 122, 161, 51, 117, 120, 70, 49, 183, 167, 66, 192, 160, 42, 149, 102, 33, 209, 67, 138, 111, 22, 87, 185, 27, 154, 175, 76, 173, 50, 62, 99, 12, 11, 65, 9, 179, 155, 181, 106, 64, 91, 194, 18, 30, 169, 126, 176, 137, 153, 101, 144, 26, 90, 206, 195, 23, 40, 95, 115, 37, 146, 129, 38, 28, 48, 2, 200, 14, 132, 130, 177, 97, 143, 123, 180, 13, 108, 156, 77, 80, 208, 109, 4, 125, 128, 46, 16, 44, 61, 69, 60, 72, 150, 6, 163, 199, 104, 114, 58, 145, 21, 78, 68, 71, 186, 84, 197, 93, 184, 127, 96, 113, 35, 36, 205, 39, 148, 55, 79, 5, 19, 116, 168, 53, 81, 135, 207, 45, 63, 191, 174, 85, 164, 157, 24, 131, 178, 188, 92, 25, 151, 98, 136, 124, 171, 15, 202, 41, 203, 82, 34, 20, 17, 182, 166, 142, 198, 133, 201, 107, 140, 32, 7, 8, 172, 59, 152, 73, 141, 83, 119, 94, 134, 159, 187, 75, 118, 165, 56, 100, 52, 1, 74, 31, 193, 189, 162, 3, 103, 105, 29, 139, 147, 158, 47, 88, 89, 204, 0]], Length: 211\n",
      "Robot Routes: [[[44, 61, 69, 60, 72, 150, 6, 163, 199, 104, 114, 58], [28, 48, 2, 200, 14, 132, 130, 177, 97, 143, 123, 180], [0, 86, 196, 121, 43, 112, 54, 57, 170, 10, 190, 110], [13, 108, 156, 77, 80, 208, 109, 4, 125, 128, 46, 16], [32, 7, 8, 172, 59, 152, 73, 141, 83, 119, 94, 134], [164, 157, 24, 131, 178, 188, 92, 25, 151, 98, 136, 124], [15, 202, 41, 203, 82, 34, 20, 17, 182, 166, 142, 198], [165, 56, 100, 52, 1, 74, 31, 193, 189, 162, 3, 103], [42, 149, 102, 33, 209, 67, 138, 111, 22, 87, 185, 27]]]\n",
      "Route: [0, 110, 122, 161, 51, 117, 120, 70, 49, 183, 167, 66, 192, 160, 42, 27, 154, 175, 76, 173, 50, 62, 99, 12, 11, 65, 9, 179, 155, 181, 106, 64, 91, 194, 18, 30, 169, 126, 176, 137, 153, 101, 144, 26, 90, 206, 195, 23, 40, 95, 115, 37, 146, 129, 38, 28, 180, 13, 16, 44, 58, 145, 21, 78, 68, 71, 186, 84, 197, 93, 184, 127, 96, 113, 35, 36, 205, 39, 148, 55, 79, 5, 19, 116, 168, 53, 81, 135, 207, 45, 63, 191, 174, 85, 164, 124, 171, 15, 198, 133, 201, 107, 140, 32, 134, 159, 187, 75, 118, 165, 103, 105, 29, 139, 147, 158, 47, 88, 89, 204, 0], Robot Group: [[44, 61, 69, 60, 72, 150, 6, 163, 199, 104, 114, 58], [28, 48, 2, 200, 14, 132, 130, 177, 97, 143, 123, 180], [0, 86, 196, 121, 43, 112, 54, 57, 170, 10, 190, 110], [13, 108, 156, 77, 80, 208, 109, 4, 125, 128, 46, 16], [32, 7, 8, 172, 59, 152, 73, 141, 83, 119, 94, 134], [164, 157, 24, 131, 178, 188, 92, 25, 151, 98, 136, 124], [15, 202, 41, 203, 82, 34, 20, 17, 182, 166, 142, 198], [165, 56, 100, 52, 1, 74, 31, 193, 189, 162, 3, 103], [42, 149, 102, 33, 209, 67, 138, 111, 22, 87, 185, 27]]\n",
      "Vehicle 0: 56691 m, 361.803 min, including 83.112 mins waiting time.\n",
      "Total distance of all routes: : 56691 m\n",
      "Maximum travel time: 361.803 min\n",
      "Trial 27...\n",
      "VRP\n",
      "Routes: [[0, 47, 112, 29, 87, 89, 171, 126, 208, 175, 110, 172, 101, 138, 59, 144, 191, 129, 122, 39, 145, 190, 49, 185, 136, 121, 71, 104, 2, 82, 30, 42, 92, 156, 69, 182, 135, 123, 194, 165, 61, 46, 63, 189, 79, 204, 48, 38, 75, 181, 43, 131, 96, 99, 183, 133, 125, 193, 162, 13, 37, 56, 158, 159, 90, 174, 31, 207, 167, 108, 168, 34, 176, 197, 55, 124, 93, 60, 187, 14, 16, 180, 44, 161, 166, 98, 155, 23, 160, 85, 188, 58, 119, 170, 76, 201, 173, 7, 94, 102, 202, 140, 152, 9, 1, 100, 134, 128, 109, 33, 50, 8, 83, 15, 200, 95, 132, 113, 106, 192, 199, 143, 139, 198, 32, 184, 18, 153, 68, 24, 6, 147, 141, 25, 137, 21, 114, 105, 130, 80, 62, 74, 26, 40, 151, 20, 51, 28, 195, 91, 157, 67, 107, 57, 88, 72, 17, 179, 70, 4, 115, 127, 169, 53, 120, 19, 97, 84, 142, 111, 27, 3, 186, 64, 66, 73, 177, 54, 103, 209, 149, 163, 164, 78, 35, 203, 150, 117, 154, 206, 45, 36, 22, 52, 10, 196, 65, 11, 5, 77, 146, 118, 178, 86, 205, 12, 81, 148, 41, 116, 0]], Length: 211\n",
      "Vehicle 0: 71744 m, 491.744 min, including 0 mins waiting time.\n",
      "Total distance of all routes: : 71744 m\n",
      "Maximum travel time: 491.744 min\n",
      "VRP-D\n",
      "Routes: [[0, 47, 112, 29, 87, 89, 171, 126, 208, 175, 110, 172, 101, 138, 59, 144, 191, 129, 122, 39, 145, 190, 49, 185, 136, 121, 71, 104, 2, 82, 30, 42, 92, 156, 69, 182, 135, 123, 194, 165, 61, 46, 63, 189, 79, 204, 48, 38, 75, 181, 43, 131, 96, 99, 183, 133, 125, 193, 162, 13, 37, 56, 158, 159, 90, 174, 31, 207, 167, 108, 168, 34, 176, 197, 55, 124, 93, 60, 187, 14, 16, 180, 44, 161, 166, 98, 155, 23, 160, 85, 188, 58, 119, 170, 76, 201, 173, 7, 94, 102, 202, 140, 152, 9, 1, 100, 134, 128, 109, 33, 50, 8, 83, 15, 200, 95, 132, 113, 106, 192, 199, 143, 139, 198, 32, 184, 18, 153, 68, 24, 6, 147, 141, 25, 137, 21, 114, 105, 130, 80, 62, 74, 26, 40, 151, 20, 51, 28, 195, 91, 157, 67, 107, 57, 88, 72, 17, 179, 70, 4, 115, 127, 169, 53, 120, 19, 97, 84, 142, 111, 27, 3, 186, 64, 66, 73, 177, 54, 103, 209, 149, 163, 164, 78, 35, 203, 150, 117, 154, 206, 45, 36, 22, 52, 10, 196, 65, 11, 5, 77, 146, 118, 178, 86, 205, 12, 81, 148, 41, 116, 0]], Length: 211\n",
      "Vehicle 0: 68251 m, 469.069 min, including 12.818 mins waiting time.\n",
      "Total distance of all routes: : 68251 m\n",
      "Maximum travel time: 469.069 min\n",
      "VRP-R\n",
      "Routes: [[0, 47, 112, 29, 87, 89, 171, 126, 208, 175, 110, 172, 101, 138, 59, 144, 191, 129, 122, 39, 145, 190, 49, 185, 136, 121, 71, 104, 2, 82, 30, 42, 92, 156, 69, 182, 135, 123, 194, 165, 61, 46, 63, 189, 79, 204, 48, 38, 75, 181, 43, 131, 96, 99, 183, 133, 125, 193, 162, 13, 37, 56, 158, 159, 90, 174, 31, 207, 167, 108, 168, 34, 176, 197, 55, 124, 93, 60, 187, 14, 16, 180, 44, 161, 166, 98, 155, 23, 160, 85, 188, 58, 119, 170, 76, 201, 173, 7, 94, 102, 202, 140, 152, 9, 1, 100, 134, 128, 109, 33, 50, 8, 83, 15, 200, 95, 132, 113, 106, 192, 199, 143, 139, 198, 32, 184, 18, 153, 68, 24, 6, 147, 141, 25, 137, 21, 114, 105, 130, 80, 62, 74, 26, 40, 151, 20, 51, 28, 195, 91, 157, 67, 107, 57, 88, 72, 17, 179, 70, 4, 115, 127, 169, 53, 120, 19, 97, 84, 142, 111, 27, 3, 186, 64, 66, 73, 177, 54, 103, 209, 149, 163, 164, 78, 35, 203, 150, 117, 154, 206, 45, 36, 22, 52, 10, 196, 65, 11, 5, 77, 146, 118, 178, 86, 205, 12, 81, 148, 41, 116, 0]], Length: 211\n",
      "Robot Routes: [[[10, 196, 65, 11, 5, 77, 146, 118, 178, 86, 205, 12], [144, 191, 129, 122, 39, 145, 190, 49, 185, 136, 121, 71], [103, 209, 149, 163, 164, 78, 35, 203, 150, 117, 154, 206], [105, 130, 80, 62, 74, 26, 40, 151, 20, 51, 28, 195], [58, 119, 170, 76, 201, 173, 7, 94, 102, 202, 140, 152], [57, 88, 72, 17, 179, 70, 4, 115, 127, 169, 53, 120], [108, 168, 34, 176, 197, 55, 124, 93, 60, 187, 14, 16], [83, 15, 200, 95, 132, 113, 106, 192, 199, 143, 139, 198]]]\n",
      "Route: [0, 47, 112, 29, 87, 89, 171, 126, 208, 175, 110, 172, 101, 138, 59, 144, 71, 104, 2, 82, 30, 42, 92, 156, 69, 182, 135, 123, 194, 165, 61, 46, 63, 189, 79, 204, 48, 38, 75, 181, 43, 131, 96, 99, 183, 133, 125, 193, 162, 13, 37, 56, 158, 159, 90, 174, 31, 207, 167, 108, 16, 180, 44, 161, 166, 98, 155, 23, 160, 85, 188, 58, 152, 9, 1, 100, 134, 128, 109, 33, 50, 8, 83, 198, 32, 184, 18, 153, 68, 24, 6, 147, 141, 25, 137, 21, 114, 105, 195, 91, 157, 67, 107, 57, 120, 19, 97, 84, 142, 111, 27, 3, 186, 64, 66, 73, 177, 54, 103, 206, 45, 36, 22, 52, 10, 12, 81, 148, 41, 116, 0], Robot Group: [[10, 196, 65, 11, 5, 77, 146, 118, 178, 86, 205, 12], [144, 191, 129, 122, 39, 145, 190, 49, 185, 136, 121, 71], [103, 209, 149, 163, 164, 78, 35, 203, 150, 117, 154, 206], [105, 130, 80, 62, 74, 26, 40, 151, 20, 51, 28, 195], [58, 119, 170, 76, 201, 173, 7, 94, 102, 202, 140, 152], [57, 88, 72, 17, 179, 70, 4, 115, 127, 169, 53, 120], [108, 168, 34, 176, 197, 55, 124, 93, 60, 187, 14, 16], [83, 15, 200, 95, 132, 113, 106, 192, 199, 143, 139, 198]]\n",
      "Vehicle 0: 61337 m, 447.083 min, including 125.746 mins waiting time.\n",
      "Total distance of all routes: : 61337 m\n",
      "Maximum travel time: 447.083 min\n",
      "VRP-RD\n",
      "Routes: [[0, 47, 112, 29, 87, 89, 171, 126, 208, 175, 110, 172, 101, 138, 59, 144, 191, 129, 122, 39, 145, 190, 49, 185, 136, 121, 71, 104, 2, 82, 30, 42, 92, 156, 69, 182, 135, 123, 194, 165, 61, 46, 63, 189, 79, 204, 48, 38, 75, 181, 43, 131, 96, 99, 183, 133, 125, 193, 162, 13, 37, 56, 158, 159, 90, 174, 31, 207, 167, 108, 168, 34, 176, 197, 55, 124, 93, 60, 187, 14, 16, 180, 44, 161, 166, 98, 155, 23, 160, 85, 188, 58, 119, 170, 76, 201, 173, 7, 94, 102, 202, 140, 152, 9, 1, 100, 134, 128, 109, 33, 50, 8, 83, 15, 200, 95, 132, 113, 106, 192, 199, 143, 139, 198, 32, 184, 18, 153, 68, 24, 6, 147, 141, 25, 137, 21, 114, 105, 130, 80, 62, 74, 26, 40, 151, 20, 51, 28, 195, 91, 157, 67, 107, 57, 88, 72, 17, 179, 70, 4, 115, 127, 169, 53, 120, 19, 97, 84, 142, 111, 27, 3, 186, 64, 66, 73, 177, 54, 103, 209, 149, 163, 164, 78, 35, 203, 150, 117, 154, 206, 45, 36, 22, 52, 10, 196, 65, 11, 5, 77, 146, 118, 178, 86, 205, 12, 81, 148, 41, 116, 0]], Length: 211\n",
      "Robot Routes: [[[10, 196, 65, 11, 5, 77, 146, 118, 178, 86, 205, 12], [144, 191, 129, 122, 39, 145, 190, 49, 185, 136, 121, 71], [103, 209, 149, 163, 164, 78, 35, 203, 150, 117, 154, 206], [105, 130, 80, 62, 74, 26, 40, 151, 20, 51, 28, 195], [58, 119, 170, 76, 201, 173, 7, 94, 102, 202, 140, 152], [57, 88, 72, 17, 179, 70, 4, 115, 127, 169, 53, 120], [108, 168, 34, 176, 197, 55, 124, 93, 60, 187, 14, 16], [83, 15, 200, 95, 132, 113, 106, 192, 199, 143, 139, 198]]]\n",
      "Route: [0, 47, 112, 29, 87, 89, 171, 126, 208, 175, 110, 172, 101, 138, 59, 144, 71, 104, 2, 82, 30, 42, 92, 156, 69, 182, 135, 123, 194, 165, 61, 46, 63, 189, 79, 204, 48, 38, 75, 181, 43, 131, 96, 99, 183, 133, 125, 193, 162, 13, 37, 56, 158, 159, 90, 174, 31, 207, 167, 108, 16, 180, 44, 161, 166, 98, 155, 23, 160, 85, 188, 58, 152, 9, 1, 100, 134, 128, 109, 33, 50, 8, 83, 198, 32, 184, 18, 153, 68, 24, 6, 147, 141, 25, 137, 21, 114, 105, 195, 91, 157, 67, 107, 57, 120, 19, 97, 84, 142, 111, 27, 3, 186, 64, 66, 73, 177, 54, 103, 206, 45, 36, 22, 52, 10, 12, 81, 148, 41, 116, 0], Robot Group: [[10, 196, 65, 11, 5, 77, 146, 118, 178, 86, 205, 12], [144, 191, 129, 122, 39, 145, 190, 49, 185, 136, 121, 71], [103, 209, 149, 163, 164, 78, 35, 203, 150, 117, 154, 206], [105, 130, 80, 62, 74, 26, 40, 151, 20, 51, 28, 195], [58, 119, 170, 76, 201, 173, 7, 94, 102, 202, 140, 152], [57, 88, 72, 17, 179, 70, 4, 115, 127, 169, 53, 120], [108, 168, 34, 176, 197, 55, 124, 93, 60, 187, 14, 16], [83, 15, 200, 95, 132, 113, 106, 192, 199, 143, 139, 198]]\n",
      "Vehicle 0: 59147 m, 437.697 min, including 136.55 mins waiting time.\n",
      "Total distance of all routes: : 59147 m\n",
      "Maximum travel time: 437.697 min\n",
      "Trial 28...\n",
      "VRP\n",
      "Routes: [[0, 49, 160, 45, 166, 131, 34, 145, 29, 20, 37, 123, 134, 149, 96, 122, 190, 36, 155, 77, 154, 86, 46, 171, 208, 118, 52, 144, 51, 129, 146, 14, 189, 209, 157, 203, 93, 69, 79, 48, 120, 27, 84, 137, 136, 12, 94, 63, 179, 192, 5, 126, 17, 132, 156, 153, 24, 148, 76, 135, 2, 70, 47, 181, 67, 110, 19, 197, 56, 158, 105, 198, 205, 32, 150, 161, 83, 21, 164, 170, 54, 104, 80, 55, 31, 3, 85, 43, 59, 18, 141, 186, 187, 182, 151, 60, 6, 130, 102, 89, 9, 199, 10, 200, 180, 41, 184, 188, 194, 196, 133, 107, 176, 13, 109, 35, 71, 44, 39, 97, 113, 111, 193, 117, 169, 183, 173, 116, 61, 185, 75, 103, 147, 159, 87, 125, 178, 143, 26, 68, 99, 124, 58, 91, 33, 88, 92, 95, 101, 174, 72, 42, 40, 172, 78, 1, 7, 11, 175, 140, 81, 15, 100, 165, 142, 195, 28, 98, 65, 23, 207, 163, 127, 152, 128, 202, 204, 73, 106, 162, 50, 168, 4, 30, 177, 139, 167, 57, 62, 201, 90, 53, 121, 8, 108, 74, 16, 112, 82, 64, 206, 66, 119, 114, 138, 22, 115, 38, 25, 191, 0]], Length: 211\n",
      "Vehicle 0: 73428 m, 493.428 min, including 0 mins waiting time.\n",
      "Total distance of all routes: : 73428 m\n",
      "Maximum travel time: 493.428 min\n",
      "VRP-D\n",
      "Routes: [[0, 49, 160, 45, 166, 131, 34, 145, 29, 20, 37, 123, 134, 149, 96, 122, 190, 36, 155, 77, 154, 86, 46, 171, 208, 118, 52, 144, 51, 129, 146, 14, 189, 209, 157, 203, 93, 69, 79, 48, 120, 27, 84, 137, 136, 12, 94, 63, 179, 192, 5, 126, 17, 132, 156, 153, 24, 148, 76, 135, 2, 70, 47, 181, 67, 110, 19, 197, 56, 158, 105, 198, 205, 32, 150, 161, 83, 21, 164, 170, 54, 104, 80, 55, 31, 3, 85, 43, 59, 18, 141, 186, 187, 182, 151, 60, 6, 130, 102, 89, 9, 199, 10, 200, 180, 41, 184, 188, 194, 196, 133, 107, 176, 13, 109, 35, 71, 44, 39, 97, 113, 111, 193, 117, 169, 183, 173, 116, 61, 185, 75, 103, 147, 159, 87, 125, 178, 143, 26, 68, 99, 124, 58, 91, 33, 88, 92, 95, 101, 174, 72, 42, 40, 172, 78, 1, 7, 11, 175, 140, 81, 15, 100, 165, 142, 195, 28, 98, 65, 23, 207, 163, 127, 152, 128, 202, 204, 73, 106, 162, 50, 168, 4, 30, 177, 139, 167, 57, 62, 201, 90, 53, 121, 8, 108, 74, 16, 112, 82, 64, 206, 66, 119, 114, 138, 22, 115, 38, 25, 191, 0]], Length: 211\n",
      "Vehicle 0: 70552 m, 468.473 min, including 13.921 mins waiting time.\n",
      "Total distance of all routes: : 70552 m\n",
      "Maximum travel time: 468.473 min\n",
      "VRP-R\n",
      "Routes: [[0, 49, 160, 45, 166, 131, 34, 145, 29, 20, 37, 123, 134, 149, 96, 122, 190, 36, 155, 77, 154, 86, 46, 171, 208, 118, 52, 144, 51, 129, 146, 14, 189, 209, 157, 203, 93, 69, 79, 48, 120, 27, 84, 137, 136, 12, 94, 63, 179, 192, 5, 126, 17, 132, 156, 153, 24, 148, 76, 135, 2, 70, 47, 181, 67, 110, 19, 197, 56, 158, 105, 198, 205, 32, 150, 161, 83, 21, 164, 170, 54, 104, 80, 55, 31, 3, 85, 43, 59, 18, 141, 186, 187, 182, 151, 60, 6, 130, 102, 89, 9, 199, 10, 200, 180, 41, 184, 188, 194, 196, 133, 107, 176, 13, 109, 35, 71, 44, 39, 97, 113, 111, 193, 117, 169, 183, 173, 116, 61, 185, 75, 103, 147, 159, 87, 125, 178, 143, 26, 68, 99, 124, 58, 91, 33, 88, 92, 95, 101, 174, 72, 42, 40, 172, 78, 1, 7, 11, 175, 140, 81, 15, 100, 165, 142, 195, 28, 98, 65, 23, 207, 163, 127, 152, 128, 202, 204, 73, 106, 162, 50, 168, 4, 30, 177, 139, 167, 57, 62, 201, 90, 53, 121, 8, 108, 74, 16, 112, 82, 64, 206, 66, 119, 114, 138, 22, 115, 38, 25, 191, 0]], Length: 211\n",
      "Robot Routes: [[[99, 124, 58, 91, 33, 88, 92, 95, 101, 174, 72, 42], [173, 116, 61, 185, 75, 103, 147, 159, 87, 125, 178, 143], [90, 53, 121, 8, 108, 74, 16, 112, 82, 64, 206, 66], [175, 140, 81, 15, 100, 165, 142, 195, 28, 98, 65, 23], [156, 153, 24, 148, 76, 135, 2, 70, 47, 181, 67, 110], [163, 127, 152, 128, 202, 204, 73, 106, 162, 50, 168, 4]]]\n",
      "Route: [0, 49, 160, 45, 166, 131, 34, 145, 29, 20, 37, 123, 134, 149, 96, 122, 190, 36, 155, 77, 154, 86, 46, 171, 208, 118, 52, 144, 51, 129, 146, 14, 189, 209, 157, 203, 93, 69, 79, 48, 120, 27, 84, 137, 136, 12, 94, 63, 179, 192, 5, 126, 17, 132, 156, 110, 19, 197, 56, 158, 105, 198, 205, 32, 150, 161, 83, 21, 164, 170, 54, 104, 80, 55, 31, 3, 85, 43, 59, 18, 141, 186, 187, 182, 151, 60, 6, 130, 102, 89, 9, 199, 10, 200, 180, 41, 184, 188, 194, 196, 133, 107, 176, 13, 109, 35, 71, 44, 39, 97, 113, 111, 193, 117, 169, 183, 173, 143, 26, 68, 99, 42, 40, 172, 78, 1, 7, 11, 175, 23, 207, 163, 4, 30, 177, 139, 167, 57, 62, 201, 90, 66, 119, 114, 138, 22, 115, 38, 25, 191, 0], Robot Group: [[99, 124, 58, 91, 33, 88, 92, 95, 101, 174, 72, 42], [173, 116, 61, 185, 75, 103, 147, 159, 87, 125, 178, 143], [90, 53, 121, 8, 108, 74, 16, 112, 82, 64, 206, 66], [175, 140, 81, 15, 100, 165, 142, 195, 28, 98, 65, 23], [156, 153, 24, 148, 76, 135, 2, 70, 47, 181, 67, 110], [163, 127, 152, 128, 202, 204, 73, 106, 162, 50, 168, 4]]\n",
      "Vehicle 0: 65556 m, 425.603 min, including 60.047 mins waiting time.\n",
      "Total distance of all routes: : 65556 m\n",
      "Maximum travel time: 425.603 min\n",
      "VRP-RD\n",
      "Routes: [[0, 49, 160, 45, 166, 131, 34, 145, 29, 20, 37, 123, 134, 149, 96, 122, 190, 36, 155, 77, 154, 86, 46, 171, 208, 118, 52, 144, 51, 129, 146, 14, 189, 209, 157, 203, 93, 69, 79, 48, 120, 27, 84, 137, 136, 12, 94, 63, 179, 192, 5, 126, 17, 132, 156, 153, 24, 148, 76, 135, 2, 70, 47, 181, 67, 110, 19, 197, 56, 158, 105, 198, 205, 32, 150, 161, 83, 21, 164, 170, 54, 104, 80, 55, 31, 3, 85, 43, 59, 18, 141, 186, 187, 182, 151, 60, 6, 130, 102, 89, 9, 199, 10, 200, 180, 41, 184, 188, 194, 196, 133, 107, 176, 13, 109, 35, 71, 44, 39, 97, 113, 111, 193, 117, 169, 183, 173, 116, 61, 185, 75, 103, 147, 159, 87, 125, 178, 143, 26, 68, 99, 124, 58, 91, 33, 88, 92, 95, 101, 174, 72, 42, 40, 172, 78, 1, 7, 11, 175, 140, 81, 15, 100, 165, 142, 195, 28, 98, 65, 23, 207, 163, 127, 152, 128, 202, 204, 73, 106, 162, 50, 168, 4, 30, 177, 139, 167, 57, 62, 201, 90, 53, 121, 8, 108, 74, 16, 112, 82, 64, 206, 66, 119, 114, 138, 22, 115, 38, 25, 191, 0]], Length: 211\n",
      "Robot Routes: [[[99, 124, 58, 91, 33, 88, 92, 95, 101, 174, 72, 42], [173, 116, 61, 185, 75, 103, 147, 159, 87, 125, 178, 143], [90, 53, 121, 8, 108, 74, 16, 112, 82, 64, 206, 66], [175, 140, 81, 15, 100, 165, 142, 195, 28, 98, 65, 23], [156, 153, 24, 148, 76, 135, 2, 70, 47, 181, 67, 110], [163, 127, 152, 128, 202, 204, 73, 106, 162, 50, 168, 4]]]\n",
      "Route: [0, 49, 160, 45, 166, 131, 34, 145, 29, 20, 37, 123, 134, 149, 96, 122, 190, 36, 155, 77, 154, 86, 46, 171, 208, 118, 52, 144, 51, 129, 146, 14, 189, 209, 157, 203, 93, 69, 79, 48, 120, 27, 84, 137, 136, 12, 94, 63, 179, 192, 5, 126, 17, 132, 156, 110, 19, 197, 56, 158, 105, 198, 205, 32, 150, 161, 83, 21, 164, 170, 54, 104, 80, 55, 31, 3, 85, 43, 59, 18, 141, 186, 187, 182, 151, 60, 6, 130, 102, 89, 9, 199, 10, 200, 180, 41, 184, 188, 194, 196, 133, 107, 176, 13, 109, 35, 71, 44, 39, 97, 113, 111, 193, 117, 169, 183, 173, 143, 26, 68, 99, 42, 40, 172, 78, 1, 7, 11, 175, 23, 207, 163, 4, 30, 177, 139, 167, 57, 62, 201, 90, 66, 119, 114, 138, 22, 115, 38, 25, 191, 0], Robot Group: [[99, 124, 58, 91, 33, 88, 92, 95, 101, 174, 72, 42], [173, 116, 61, 185, 75, 103, 147, 159, 87, 125, 178, 143], [90, 53, 121, 8, 108, 74, 16, 112, 82, 64, 206, 66], [175, 140, 81, 15, 100, 165, 142, 195, 28, 98, 65, 23], [156, 153, 24, 148, 76, 135, 2, 70, 47, 181, 67, 110], [163, 127, 152, 128, 202, 204, 73, 106, 162, 50, 168, 4]]\n",
      "Vehicle 0: 63579 m, 417.316 min, including 79.737 mins waiting time.\n",
      "Total distance of all routes: : 63579 m\n",
      "Maximum travel time: 417.316 min\n",
      "Trial 29...\n",
      "VRP\n",
      "Routes: [[0, 204, 191, 105, 178, 1, 108, 167, 36, 75, 95, 207, 50, 33, 157, 132, 8, 172, 129, 89, 78, 142, 146, 189, 137, 54, 30, 97, 208, 116, 195, 192, 70, 56, 61, 111, 66, 164, 57, 13, 23, 44, 87, 11, 162, 10, 206, 126, 73, 106, 48, 29, 165, 85, 46, 60, 32, 182, 194, 166, 119, 190, 143, 26, 2, 37, 52, 121, 82, 100, 152, 69, 18, 160, 76, 92, 43, 118, 170, 68, 102, 161, 144, 12, 177, 179, 6, 131, 176, 181, 112, 20, 64, 3, 139, 80, 25, 114, 154, 188, 168, 199, 59, 9, 19, 193, 133, 180, 140, 47, 28, 90, 7, 14, 51, 163, 83, 22, 124, 138, 93, 135, 99, 77, 197, 187, 38, 159, 107, 63, 55, 71, 156, 45, 209, 40, 79, 185, 148, 149, 15, 122, 196, 53, 35, 16, 201, 96, 134, 58, 65, 128, 186, 103, 49, 88, 115, 39, 24, 84, 31, 158, 113, 62, 74, 104, 72, 184, 42, 17, 175, 123, 141, 145, 155, 127, 125, 109, 117, 136, 183, 101, 205, 147, 120, 150, 202, 200, 98, 130, 41, 94, 198, 27, 173, 151, 34, 91, 81, 5, 67, 4, 86, 21, 174, 153, 169, 171, 203, 110, 0]], Length: 211\n",
      "Vehicle 0: 70243 m, 490.243 min, including 0 mins waiting time.\n",
      "Total distance of all routes: : 70243 m\n",
      "Maximum travel time: 490.243 min\n",
      "VRP-D\n",
      "Routes: [[0, 204, 191, 105, 178, 1, 108, 167, 36, 75, 95, 207, 50, 33, 157, 132, 8, 172, 129, 89, 78, 142, 146, 189, 137, 54, 30, 97, 208, 116, 195, 192, 70, 56, 61, 111, 66, 164, 57, 13, 23, 44, 87, 11, 162, 10, 206, 126, 73, 106, 48, 29, 165, 85, 46, 60, 32, 182, 194, 166, 119, 190, 143, 26, 2, 37, 52, 121, 82, 100, 152, 69, 18, 160, 76, 92, 43, 118, 170, 68, 102, 161, 144, 12, 177, 179, 6, 131, 176, 181, 112, 20, 64, 3, 139, 80, 25, 114, 154, 188, 168, 199, 59, 9, 19, 193, 133, 180, 140, 47, 28, 90, 7, 14, 51, 163, 83, 22, 124, 138, 93, 135, 99, 77, 197, 187, 38, 159, 107, 63, 55, 71, 156, 45, 209, 40, 79, 185, 148, 149, 15, 122, 196, 53, 35, 16, 201, 96, 134, 58, 65, 128, 186, 103, 49, 88, 115, 39, 24, 84, 31, 158, 113, 62, 74, 104, 72, 184, 42, 17, 175, 123, 141, 145, 155, 127, 125, 109, 117, 136, 183, 101, 205, 147, 120, 150, 202, 200, 98, 130, 41, 94, 198, 27, 173, 151, 34, 91, 81, 5, 67, 4, 86, 21, 174, 153, 169, 171, 203, 110, 0]], Length: 211\n",
      "Vehicle 0: 67709 m, 467.578 min, including 11.869 mins waiting time.\n",
      "Total distance of all routes: : 67709 m\n",
      "Maximum travel time: 467.578 min\n",
      "VRP-R\n",
      "Routes: [[0, 204, 191, 105, 178, 1, 108, 167, 36, 75, 95, 207, 50, 33, 157, 132, 8, 172, 129, 89, 78, 142, 146, 189, 137, 54, 30, 97, 208, 116, 195, 192, 70, 56, 61, 111, 66, 164, 57, 13, 23, 44, 87, 11, 162, 10, 206, 126, 73, 106, 48, 29, 165, 85, 46, 60, 32, 182, 194, 166, 119, 190, 143, 26, 2, 37, 52, 121, 82, 100, 152, 69, 18, 160, 76, 92, 43, 118, 170, 68, 102, 161, 144, 12, 177, 179, 6, 131, 176, 181, 112, 20, 64, 3, 139, 80, 25, 114, 154, 188, 168, 199, 59, 9, 19, 193, 133, 180, 140, 47, 28, 90, 7, 14, 51, 163, 83, 22, 124, 138, 93, 135, 99, 77, 197, 187, 38, 159, 107, 63, 55, 71, 156, 45, 209, 40, 79, 185, 148, 149, 15, 122, 196, 53, 35, 16, 201, 96, 134, 58, 65, 128, 186, 103, 49, 88, 115, 39, 24, 84, 31, 158, 113, 62, 74, 104, 72, 184, 42, 17, 175, 123, 141, 145, 155, 127, 125, 109, 117, 136, 183, 101, 205, 147, 120, 150, 202, 200, 98, 130, 41, 94, 198, 27, 173, 151, 34, 91, 81, 5, 67, 4, 86, 21, 174, 153, 169, 171, 203, 110, 0]], Length: 211\n",
      "Robot Routes: [[[118, 170, 68, 102, 161, 144, 12, 177, 179, 6, 131, 176], [30, 97, 208, 116, 195, 192, 70, 56, 61, 111, 66, 164], [81, 5, 67, 4, 86, 21, 174, 153, 169, 171, 203, 110], [191, 105, 178, 1, 108, 167, 36, 75, 95, 207, 50, 33], [73, 106, 48, 29, 165, 85, 46, 60, 32, 182, 194, 166], [140, 47, 28, 90, 7, 14, 51, 163, 83, 22, 124, 138], [103, 49, 88, 115, 39, 24, 84, 31, 158, 113, 62, 74]]]\n",
      "Route: [0, 204, 191, 33, 157, 132, 8, 172, 129, 89, 78, 142, 146, 189, 137, 54, 30, 164, 57, 13, 23, 44, 87, 11, 162, 10, 206, 126, 73, 166, 119, 190, 143, 26, 2, 37, 52, 121, 82, 100, 152, 69, 18, 160, 76, 92, 43, 118, 176, 181, 112, 20, 64, 3, 139, 80, 25, 114, 154, 188, 168, 199, 59, 9, 19, 193, 133, 180, 140, 138, 93, 135, 99, 77, 197, 187, 38, 159, 107, 63, 55, 71, 156, 45, 209, 40, 79, 185, 148, 149, 15, 122, 196, 53, 35, 16, 201, 96, 134, 58, 65, 128, 186, 103, 74, 104, 72, 184, 42, 17, 175, 123, 141, 145, 155, 127, 125, 109, 117, 136, 183, 101, 205, 147, 120, 150, 202, 200, 98, 130, 41, 94, 198, 27, 173, 151, 34, 91, 81, 110, 0], Robot Group: [[118, 170, 68, 102, 161, 144, 12, 177, 179, 6, 131, 176], [30, 97, 208, 116, 195, 192, 70, 56, 61, 111, 66, 164], [81, 5, 67, 4, 86, 21, 174, 153, 169, 171, 203, 110], [191, 105, 178, 1, 108, 167, 36, 75, 95, 207, 50, 33], [73, 106, 48, 29, 165, 85, 46, 60, 32, 182, 194, 166], [140, 47, 28, 90, 7, 14, 51, 163, 83, 22, 124, 138], [103, 49, 88, 115, 39, 24, 84, 31, 158, 113, 62, 74]]\n",
      "Vehicle 0: 60346 m, 342.081 min, including 1.735 mins waiting time.\n",
      "Total distance of all routes: : 60346 m\n",
      "Maximum travel time: 342.081 min\n",
      "VRP-RD\n",
      "Routes: [[0, 204, 191, 105, 178, 1, 108, 167, 36, 75, 95, 207, 50, 33, 157, 132, 8, 172, 129, 89, 78, 142, 146, 189, 137, 54, 30, 97, 208, 116, 195, 192, 70, 56, 61, 111, 66, 164, 57, 13, 23, 44, 87, 11, 162, 10, 206, 126, 73, 106, 48, 29, 165, 85, 46, 60, 32, 182, 194, 166, 119, 190, 143, 26, 2, 37, 52, 121, 82, 100, 152, 69, 18, 160, 76, 92, 43, 118, 170, 68, 102, 161, 144, 12, 177, 179, 6, 131, 176, 181, 112, 20, 64, 3, 139, 80, 25, 114, 154, 188, 168, 199, 59, 9, 19, 193, 133, 180, 140, 47, 28, 90, 7, 14, 51, 163, 83, 22, 124, 138, 93, 135, 99, 77, 197, 187, 38, 159, 107, 63, 55, 71, 156, 45, 209, 40, 79, 185, 148, 149, 15, 122, 196, 53, 35, 16, 201, 96, 134, 58, 65, 128, 186, 103, 49, 88, 115, 39, 24, 84, 31, 158, 113, 62, 74, 104, 72, 184, 42, 17, 175, 123, 141, 145, 155, 127, 125, 109, 117, 136, 183, 101, 205, 147, 120, 150, 202, 200, 98, 130, 41, 94, 198, 27, 173, 151, 34, 91, 81, 5, 67, 4, 86, 21, 174, 153, 169, 171, 203, 110, 0]], Length: 211\n",
      "Robot Routes: [[[118, 170, 68, 102, 161, 144, 12, 177, 179, 6, 131, 176], [30, 97, 208, 116, 195, 192, 70, 56, 61, 111, 66, 164], [81, 5, 67, 4, 86, 21, 174, 153, 169, 171, 203, 110], [191, 105, 178, 1, 108, 167, 36, 75, 95, 207, 50, 33], [73, 106, 48, 29, 165, 85, 46, 60, 32, 182, 194, 166], [140, 47, 28, 90, 7, 14, 51, 163, 83, 22, 124, 138], [103, 49, 88, 115, 39, 24, 84, 31, 158, 113, 62, 74]]]\n",
      "Route: [0, 204, 191, 33, 157, 132, 8, 172, 129, 89, 78, 142, 146, 189, 137, 54, 30, 164, 57, 13, 23, 44, 87, 11, 162, 10, 206, 126, 73, 166, 119, 190, 143, 26, 2, 37, 52, 121, 82, 100, 152, 69, 18, 160, 76, 92, 43, 118, 176, 181, 112, 20, 64, 3, 139, 80, 25, 114, 154, 188, 168, 199, 59, 9, 19, 193, 133, 180, 140, 138, 93, 135, 99, 77, 197, 187, 38, 159, 107, 63, 55, 71, 156, 45, 209, 40, 79, 185, 148, 149, 15, 122, 196, 53, 35, 16, 201, 96, 134, 58, 65, 128, 186, 103, 74, 104, 72, 184, 42, 17, 175, 123, 141, 145, 155, 127, 125, 109, 117, 136, 183, 101, 205, 147, 120, 150, 202, 200, 98, 130, 41, 94, 198, 27, 173, 151, 34, 91, 81, 110, 0], Robot Group: [[118, 170, 68, 102, 161, 144, 12, 177, 179, 6, 131, 176], [30, 97, 208, 116, 195, 192, 70, 56, 61, 111, 66, 164], [81, 5, 67, 4, 86, 21, 174, 153, 169, 171, 203, 110], [191, 105, 178, 1, 108, 167, 36, 75, 95, 207, 50, 33], [73, 106, 48, 29, 165, 85, 46, 60, 32, 182, 194, 166], [140, 47, 28, 90, 7, 14, 51, 163, 83, 22, 124, 138], [103, 49, 88, 115, 39, 24, 84, 31, 158, 113, 62, 74]]\n",
      "Vehicle 0: 59110 m, 327.884 min, including 10.774 mins waiting time.\n",
      "Total distance of all routes: : 59110 m\n",
      "Maximum travel time: 327.884 min\n",
      "Trial 30...\n",
      "VRP\n",
      "Routes: [[0, 171, 166, 200, 26, 78, 77, 9, 3, 137, 136, 130, 15, 184, 189, 134, 6, 158, 32, 159, 75, 13, 110, 84, 50, 129, 29, 18, 33, 199, 121, 170, 138, 127, 17, 145, 156, 107, 85, 172, 198, 19, 124, 175, 122, 64, 25, 104, 30, 76, 205, 58, 147, 96, 105, 55, 56, 66, 4, 71, 113, 80, 164, 180, 95, 57, 97, 89, 132, 5, 197, 10, 150, 109, 128, 123, 207, 22, 1, 8, 63, 20, 12, 169, 119, 152, 111, 157, 53, 125, 196, 60, 161, 39, 165, 49, 120, 144, 108, 16, 51, 143, 160, 90, 7, 11, 185, 203, 117, 82, 106, 148, 188, 176, 42, 155, 135, 174, 192, 83, 74, 72, 59, 98, 202, 36, 48, 37, 14, 177, 194, 69, 118, 87, 44, 99, 46, 54, 103, 31, 149, 88, 182, 162, 179, 195, 102, 100, 24, 193, 183, 47, 61, 141, 112, 68, 131, 91, 86, 209, 190, 28, 2, 191, 140, 139, 178, 142, 73, 181, 27, 38, 94, 173, 126, 65, 34, 35, 201, 168, 92, 163, 67, 151, 62, 79, 116, 206, 208, 93, 114, 154, 70, 41, 167, 45, 81, 23, 52, 187, 133, 43, 40, 21, 146, 186, 115, 204, 101, 153, 0]], Length: 211\n",
      "Vehicle 0: 71259 m, 491.259 min, including 0 mins waiting time.\n",
      "Total distance of all routes: : 71259 m\n",
      "Maximum travel time: 491.259 min\n",
      "VRP-D\n",
      "Routes: [[0, 171, 166, 200, 26, 78, 77, 9, 3, 137, 136, 130, 15, 184, 189, 134, 6, 158, 32, 159, 75, 13, 110, 84, 50, 129, 29, 18, 33, 199, 121, 170, 138, 127, 17, 145, 156, 107, 85, 172, 198, 19, 124, 175, 122, 64, 25, 104, 30, 76, 205, 58, 147, 96, 105, 55, 56, 66, 4, 71, 113, 80, 164, 180, 95, 57, 97, 89, 132, 5, 197, 10, 150, 109, 128, 123, 207, 22, 1, 8, 63, 20, 12, 169, 119, 152, 111, 157, 53, 125, 196, 60, 161, 39, 165, 49, 120, 144, 108, 16, 51, 143, 160, 90, 7, 11, 185, 203, 117, 82, 106, 148, 188, 176, 42, 155, 135, 174, 192, 83, 74, 72, 59, 98, 202, 36, 48, 37, 14, 177, 194, 69, 118, 87, 44, 99, 46, 54, 103, 31, 149, 88, 182, 162, 179, 195, 102, 100, 24, 193, 183, 47, 61, 141, 112, 68, 131, 91, 86, 209, 190, 28, 2, 191, 140, 139, 178, 142, 73, 181, 27, 38, 94, 173, 126, 65, 34, 35, 201, 168, 92, 163, 67, 151, 62, 79, 116, 206, 208, 93, 114, 154, 70, 41, 167, 45, 81, 23, 52, 187, 133, 43, 40, 21, 146, 186, 115, 204, 101, 153, 0]], Length: 211\n",
      "Vehicle 0: 65713 m, 467.939 min, including 16.226 mins waiting time.\n",
      "Total distance of all routes: : 65713 m\n",
      "Maximum travel time: 467.939 min\n",
      "VRP-R\n",
      "Routes: [[0, 171, 166, 200, 26, 78, 77, 9, 3, 137, 136, 130, 15, 184, 189, 134, 6, 158, 32, 159, 75, 13, 110, 84, 50, 129, 29, 18, 33, 199, 121, 170, 138, 127, 17, 145, 156, 107, 85, 172, 198, 19, 124, 175, 122, 64, 25, 104, 30, 76, 205, 58, 147, 96, 105, 55, 56, 66, 4, 71, 113, 80, 164, 180, 95, 57, 97, 89, 132, 5, 197, 10, 150, 109, 128, 123, 207, 22, 1, 8, 63, 20, 12, 169, 119, 152, 111, 157, 53, 125, 196, 60, 161, 39, 165, 49, 120, 144, 108, 16, 51, 143, 160, 90, 7, 11, 185, 203, 117, 82, 106, 148, 188, 176, 42, 155, 135, 174, 192, 83, 74, 72, 59, 98, 202, 36, 48, 37, 14, 177, 194, 69, 118, 87, 44, 99, 46, 54, 103, 31, 149, 88, 182, 162, 179, 195, 102, 100, 24, 193, 183, 47, 61, 141, 112, 68, 131, 91, 86, 209, 190, 28, 2, 191, 140, 139, 178, 142, 73, 181, 27, 38, 94, 173, 126, 65, 34, 35, 201, 168, 92, 163, 67, 151, 62, 79, 116, 206, 208, 93, 114, 154, 70, 41, 167, 45, 81, 23, 52, 187, 133, 43, 40, 21, 146, 186, 115, 204, 101, 153, 0]], Length: 211\n",
      "Robot Routes: [[[99, 46, 54, 103, 31, 149, 88, 182, 162, 179, 195, 102], [60, 161, 39, 165, 49, 120, 144, 108, 16, 51, 143, 160], [79, 116, 206, 208, 93, 114, 154, 70, 41, 167, 45, 81], [124, 175, 122, 64, 25, 104, 30, 76, 205, 58, 147, 96], [100, 24, 193, 183, 47, 61, 141, 112, 68, 131, 91, 86], [159, 75, 13, 110, 84, 50, 129, 29, 18, 33, 199, 121], [73, 181, 27, 38, 94, 173, 126, 65, 34, 35, 201, 168]]]\n",
      "Route: [0, 171, 166, 200, 26, 78, 77, 9, 3, 137, 136, 130, 15, 184, 189, 134, 6, 158, 32, 159, 121, 170, 138, 127, 17, 145, 156, 107, 85, 172, 198, 19, 124, 96, 105, 55, 56, 66, 4, 71, 113, 80, 164, 180, 95, 57, 97, 89, 132, 5, 197, 10, 150, 109, 128, 123, 207, 22, 1, 8, 63, 20, 12, 169, 119, 152, 111, 157, 53, 125, 196, 60, 160, 90, 7, 11, 185, 203, 117, 82, 106, 148, 188, 176, 42, 155, 135, 174, 192, 83, 74, 72, 59, 98, 202, 36, 48, 37, 14, 177, 194, 69, 118, 87, 44, 99, 102, 100, 86, 209, 190, 28, 2, 191, 140, 139, 178, 142, 73, 168, 92, 163, 67, 151, 62, 79, 81, 23, 52, 187, 133, 43, 40, 21, 146, 186, 115, 204, 101, 153, 0], Robot Group: [[99, 46, 54, 103, 31, 149, 88, 182, 162, 179, 195, 102], [60, 161, 39, 165, 49, 120, 144, 108, 16, 51, 143, 160], [79, 116, 206, 208, 93, 114, 154, 70, 41, 167, 45, 81], [124, 175, 122, 64, 25, 104, 30, 76, 205, 58, 147, 96], [100, 24, 193, 183, 47, 61, 141, 112, 68, 131, 91, 86], [159, 75, 13, 110, 84, 50, 129, 29, 18, 33, 199, 121], [73, 181, 27, 38, 94, 173, 126, 65, 34, 35, 201, 168]]\n",
      "Vehicle 0: 63132 m, 353.857 min, including 10.725 mins waiting time.\n",
      "Total distance of all routes: : 63132 m\n",
      "Maximum travel time: 353.857 min\n",
      "VRP-RD\n",
      "Routes: [[0, 171, 166, 200, 26, 78, 77, 9, 3, 137, 136, 130, 15, 184, 189, 134, 6, 158, 32, 159, 75, 13, 110, 84, 50, 129, 29, 18, 33, 199, 121, 170, 138, 127, 17, 145, 156, 107, 85, 172, 198, 19, 124, 175, 122, 64, 25, 104, 30, 76, 205, 58, 147, 96, 105, 55, 56, 66, 4, 71, 113, 80, 164, 180, 95, 57, 97, 89, 132, 5, 197, 10, 150, 109, 128, 123, 207, 22, 1, 8, 63, 20, 12, 169, 119, 152, 111, 157, 53, 125, 196, 60, 161, 39, 165, 49, 120, 144, 108, 16, 51, 143, 160, 90, 7, 11, 185, 203, 117, 82, 106, 148, 188, 176, 42, 155, 135, 174, 192, 83, 74, 72, 59, 98, 202, 36, 48, 37, 14, 177, 194, 69, 118, 87, 44, 99, 46, 54, 103, 31, 149, 88, 182, 162, 179, 195, 102, 100, 24, 193, 183, 47, 61, 141, 112, 68, 131, 91, 86, 209, 190, 28, 2, 191, 140, 139, 178, 142, 73, 181, 27, 38, 94, 173, 126, 65, 34, 35, 201, 168, 92, 163, 67, 151, 62, 79, 116, 206, 208, 93, 114, 154, 70, 41, 167, 45, 81, 23, 52, 187, 133, 43, 40, 21, 146, 186, 115, 204, 101, 153, 0]], Length: 211\n",
      "Robot Routes: [[[99, 46, 54, 103, 31, 149, 88, 182, 162, 179, 195, 102], [60, 161, 39, 165, 49, 120, 144, 108, 16, 51, 143, 160], [79, 116, 206, 208, 93, 114, 154, 70, 41, 167, 45, 81], [124, 175, 122, 64, 25, 104, 30, 76, 205, 58, 147, 96], [100, 24, 193, 183, 47, 61, 141, 112, 68, 131, 91, 86], [159, 75, 13, 110, 84, 50, 129, 29, 18, 33, 199, 121], [73, 181, 27, 38, 94, 173, 126, 65, 34, 35, 201, 168]]]\n",
      "Route: [0, 171, 166, 200, 26, 78, 77, 9, 3, 137, 136, 130, 15, 184, 189, 134, 6, 158, 32, 159, 121, 170, 138, 127, 17, 145, 156, 107, 85, 172, 198, 19, 124, 96, 105, 55, 56, 66, 4, 71, 113, 80, 164, 180, 95, 57, 97, 89, 132, 5, 197, 10, 150, 109, 128, 123, 207, 22, 1, 8, 63, 20, 12, 169, 119, 152, 111, 157, 53, 125, 196, 60, 160, 90, 7, 11, 185, 203, 117, 82, 106, 148, 188, 176, 42, 155, 135, 174, 192, 83, 74, 72, 59, 98, 202, 36, 48, 37, 14, 177, 194, 69, 118, 87, 44, 99, 102, 100, 86, 209, 190, 28, 2, 191, 140, 139, 178, 142, 73, 168, 92, 163, 67, 151, 62, 79, 81, 23, 52, 187, 133, 43, 40, 21, 146, 186, 115, 204, 101, 153, 0], Robot Group: [[99, 46, 54, 103, 31, 149, 88, 182, 162, 179, 195, 102], [60, 161, 39, 165, 49, 120, 144, 108, 16, 51, 143, 160], [79, 116, 206, 208, 93, 114, 154, 70, 41, 167, 45, 81], [124, 175, 122, 64, 25, 104, 30, 76, 205, 58, 147, 96], [100, 24, 193, 183, 47, 61, 141, 112, 68, 131, 91, 86], [159, 75, 13, 110, 84, 50, 129, 29, 18, 33, 199, 121], [73, 181, 27, 38, 94, 173, 126, 65, 34, 35, 201, 168]]\n",
      "Vehicle 0: 59820 m, 344.186 min, including 26.366 mins waiting time.\n",
      "Total distance of all routes: : 59820 m\n",
      "Maximum travel time: 344.186 min\n",
      "\n",
      "Done!\n"
     ]
    }
   ],
   "source": [
    "# 記錄結果\n",
    "result = create_result_model()\n",
    "\n",
    "map_size = (5, 5)\n",
    "num_node = 210\n",
    "num_trial = 30\n",
    "\n",
    "# 設定實驗參數 & 實驗\n",
    "ex_controls = dict(map_size=map_size, num_nodes=num_node, num_vehicles=1, trials=num_trial)\n",
    "simulate_experiment(**ex_controls)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>map_size</th>\n",
       "      <th>num_nodes</th>\n",
       "      <th>num_locations</th>\n",
       "      <th>num_vehicles</th>\n",
       "      <th>vehicle_capacities</th>\n",
       "      <th>type</th>\n",
       "      <th>truck_routes</th>\n",
       "      <th>drone_routes</th>\n",
       "      <th>robot_routes</th>\n",
       "      <th>distances</th>\n",
       "      <th>time</th>\n",
       "      <th>waiting</th>\n",
       "      <th>dispatch</th>\n",
       "      <th>total_distance</th>\n",
       "      <th>travel_time</th>\n",
       "      <th>time_complexity</th>\n",
       "      <th>space_complexity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>(5, 5)</td>\n",
       "      <td>210</td>\n",
       "      <td>[(2.5, 2.5), (4.947, 3.071), (3.308, 2.931), (...</td>\n",
       "      <td>1</td>\n",
       "      <td>[210]</td>\n",
       "      <td>VRP</td>\n",
       "      <td>[[0, 22, 192, 10, 66, 161, 186, 136, 149, 141,...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[71461]</td>\n",
       "      <td>[491.461]</td>\n",
       "      <td>[0]</td>\n",
       "      <td>0</td>\n",
       "      <td>71461</td>\n",
       "      <td>491.461</td>\n",
       "      <td>3.4456</td>\n",
       "      <td>4.9473</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>(5, 5)</td>\n",
       "      <td>210</td>\n",
       "      <td>[(2.5, 2.5), (4.947, 3.071), (3.308, 2.931), (...</td>\n",
       "      <td>1</td>\n",
       "      <td>[210]</td>\n",
       "      <td>VRP-D</td>\n",
       "      <td>[[0, 22, 192, 10, 66, 161, 186, 136, 149, 141,...</td>\n",
       "      <td>[[[83, 78, 169], [62, 159, 129], [132, 34, 191...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[66541]</td>\n",
       "      <td>[468.401]</td>\n",
       "      <td>[15.86]</td>\n",
       "      <td>[34]</td>\n",
       "      <td>66541</td>\n",
       "      <td>468.401</td>\n",
       "      <td>3.9492</td>\n",
       "      <td>9.0293</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>(5, 5)</td>\n",
       "      <td>210</td>\n",
       "      <td>[(2.5, 2.5), (4.947, 3.071), (3.308, 2.931), (...</td>\n",
       "      <td>1</td>\n",
       "      <td>[210]</td>\n",
       "      <td>VRP-R</td>\n",
       "      <td>[[0, 106, 29, 79, 63, 68, 81, 109, 89, 32, 64,...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[[[93, 8, 165, 146, 113, 197, 168, 67, 11, 103...</td>\n",
       "      <td>[60636]</td>\n",
       "      <td>[391.501]</td>\n",
       "      <td>[54.865]</td>\n",
       "      <td>[16]</td>\n",
       "      <td>60636</td>\n",
       "      <td>391.501</td>\n",
       "      <td>3.3019</td>\n",
       "      <td>23.9941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>(5, 5)</td>\n",
       "      <td>210</td>\n",
       "      <td>[(2.5, 2.5), (4.947, 3.071), (3.308, 2.931), (...</td>\n",
       "      <td>1</td>\n",
       "      <td>[210]</td>\n",
       "      <td>VRP-RD</td>\n",
       "      <td>[[0, 106, 29, 79, 63, 68, 81, 109, 89, 32, 64,...</td>\n",
       "      <td>[[[83, 78, 169], [62, 159, 129], [26, 76, 87],...</td>\n",
       "      <td>[[[93, 8, 165, 146, 113, 197, 168, 67, 11, 103...</td>\n",
       "      <td>[57243]</td>\n",
       "      <td>[401.251]</td>\n",
       "      <td>[68.008]</td>\n",
       "      <td>[36]</td>\n",
       "      <td>57243</td>\n",
       "      <td>401.251</td>\n",
       "      <td>4.0676</td>\n",
       "      <td>18.9150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2</td>\n",
       "      <td>(5, 5)</td>\n",
       "      <td>210</td>\n",
       "      <td>[(2.5, 2.5), (4.74, 1.698), (0.735, 4.262), (0...</td>\n",
       "      <td>1</td>\n",
       "      <td>[210]</td>\n",
       "      <td>VRP</td>\n",
       "      <td>[[0, 193, 95, 191, 53, 198, 167, 136, 88, 91, ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[70735]</td>\n",
       "      <td>[490.735]</td>\n",
       "      <td>[0]</td>\n",
       "      <td>0</td>\n",
       "      <td>70735</td>\n",
       "      <td>490.735</td>\n",
       "      <td>6.2699</td>\n",
       "      <td>4.4912</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>29</td>\n",
       "      <td>(5, 5)</td>\n",
       "      <td>210</td>\n",
       "      <td>[(2.5, 2.5), (3.157, 2.292), (2.945, 0.163), (...</td>\n",
       "      <td>1</td>\n",
       "      <td>[210]</td>\n",
       "      <td>VRP-RD</td>\n",
       "      <td>[[0, 204, 191, 33, 157, 132, 8, 172, 129, 89, ...</td>\n",
       "      <td>[[[175, 123, 141], [138, 93, 135], [148, 149, ...</td>\n",
       "      <td>[[[118, 170, 68, 102, 161, 144, 12, 177, 179, ...</td>\n",
       "      <td>[59110]</td>\n",
       "      <td>[363.884]</td>\n",
       "      <td>[10.774]</td>\n",
       "      <td>[36]</td>\n",
       "      <td>59110</td>\n",
       "      <td>363.884</td>\n",
       "      <td>4.3262</td>\n",
       "      <td>28.9287</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>30</td>\n",
       "      <td>(5, 5)</td>\n",
       "      <td>210</td>\n",
       "      <td>[(2.5, 2.5), (0.347, 3.618), (0.367, 0.495), (...</td>\n",
       "      <td>1</td>\n",
       "      <td>[210]</td>\n",
       "      <td>VRP</td>\n",
       "      <td>[[0, 171, 166, 200, 26, 78, 77, 9, 3, 137, 136...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[71259]</td>\n",
       "      <td>[491.259]</td>\n",
       "      <td>[0]</td>\n",
       "      <td>0</td>\n",
       "      <td>71259</td>\n",
       "      <td>491.259</td>\n",
       "      <td>4.8988</td>\n",
       "      <td>4.3809</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>30</td>\n",
       "      <td>(5, 5)</td>\n",
       "      <td>210</td>\n",
       "      <td>[(2.5, 2.5), (0.347, 3.618), (0.367, 0.495), (...</td>\n",
       "      <td>1</td>\n",
       "      <td>[210]</td>\n",
       "      <td>VRP-D</td>\n",
       "      <td>[[0, 171, 166, 200, 26, 78, 77, 9, 3, 136, 130...</td>\n",
       "      <td>[[[152, 111, 157], [125, 196, 60], [172, 198, ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[65713]</td>\n",
       "      <td>[467.939]</td>\n",
       "      <td>[16.226]</td>\n",
       "      <td>[34]</td>\n",
       "      <td>65713</td>\n",
       "      <td>467.939</td>\n",
       "      <td>4.4685</td>\n",
       "      <td>6.1289</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>30</td>\n",
       "      <td>(5, 5)</td>\n",
       "      <td>210</td>\n",
       "      <td>[(2.5, 2.5), (0.347, 3.618), (0.367, 0.495), (...</td>\n",
       "      <td>1</td>\n",
       "      <td>[210]</td>\n",
       "      <td>VRP-R</td>\n",
       "      <td>[[0, 171, 166, 200, 26, 78, 77, 9, 3, 137, 136...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[[[48, 46, 54, 103, 31, 149, 88, 182, 162, 179...</td>\n",
       "      <td>[63132]</td>\n",
       "      <td>[367.857]</td>\n",
       "      <td>[10.725]</td>\n",
       "      <td>[14]</td>\n",
       "      <td>63132</td>\n",
       "      <td>367.857</td>\n",
       "      <td>4.3743</td>\n",
       "      <td>23.4141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>30</td>\n",
       "      <td>(5, 5)</td>\n",
       "      <td>210</td>\n",
       "      <td>[(2.5, 2.5), (0.347, 3.618), (0.367, 0.495), (...</td>\n",
       "      <td>1</td>\n",
       "      <td>[210]</td>\n",
       "      <td>VRP-RD</td>\n",
       "      <td>[[0, 171, 166, 200, 26, 78, 77, 9, 3, 137, 136...</td>\n",
       "      <td>[[[152, 111, 157], [125, 196, 60], [172, 198, ...</td>\n",
       "      <td>[[[48, 46, 54, 103, 31, 149, 88, 182, 162, 179...</td>\n",
       "      <td>[59820]</td>\n",
       "      <td>[380.186]</td>\n",
       "      <td>[26.366]</td>\n",
       "      <td>[36]</td>\n",
       "      <td>59820</td>\n",
       "      <td>380.186</td>\n",
       "      <td>4.6138</td>\n",
       "      <td>22.6348</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>120 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     id map_size  num_nodes  \\\n",
       "0     1   (5, 5)        210   \n",
       "1     1   (5, 5)        210   \n",
       "2     1   (5, 5)        210   \n",
       "3     1   (5, 5)        210   \n",
       "4     2   (5, 5)        210   \n",
       "..   ..      ...        ...   \n",
       "115  29   (5, 5)        210   \n",
       "116  30   (5, 5)        210   \n",
       "117  30   (5, 5)        210   \n",
       "118  30   (5, 5)        210   \n",
       "119  30   (5, 5)        210   \n",
       "\n",
       "                                         num_locations  num_vehicles  \\\n",
       "0    [(2.5, 2.5), (4.947, 3.071), (3.308, 2.931), (...             1   \n",
       "1    [(2.5, 2.5), (4.947, 3.071), (3.308, 2.931), (...             1   \n",
       "2    [(2.5, 2.5), (4.947, 3.071), (3.308, 2.931), (...             1   \n",
       "3    [(2.5, 2.5), (4.947, 3.071), (3.308, 2.931), (...             1   \n",
       "4    [(2.5, 2.5), (4.74, 1.698), (0.735, 4.262), (0...             1   \n",
       "..                                                 ...           ...   \n",
       "115  [(2.5, 2.5), (3.157, 2.292), (2.945, 0.163), (...             1   \n",
       "116  [(2.5, 2.5), (0.347, 3.618), (0.367, 0.495), (...             1   \n",
       "117  [(2.5, 2.5), (0.347, 3.618), (0.367, 0.495), (...             1   \n",
       "118  [(2.5, 2.5), (0.347, 3.618), (0.367, 0.495), (...             1   \n",
       "119  [(2.5, 2.5), (0.347, 3.618), (0.367, 0.495), (...             1   \n",
       "\n",
       "    vehicle_capacities    type  \\\n",
       "0                [210]     VRP   \n",
       "1                [210]   VRP-D   \n",
       "2                [210]   VRP-R   \n",
       "3                [210]  VRP-RD   \n",
       "4                [210]     VRP   \n",
       "..                 ...     ...   \n",
       "115              [210]  VRP-RD   \n",
       "116              [210]     VRP   \n",
       "117              [210]   VRP-D   \n",
       "118              [210]   VRP-R   \n",
       "119              [210]  VRP-RD   \n",
       "\n",
       "                                          truck_routes  \\\n",
       "0    [[0, 22, 192, 10, 66, 161, 186, 136, 149, 141,...   \n",
       "1    [[0, 22, 192, 10, 66, 161, 186, 136, 149, 141,...   \n",
       "2    [[0, 106, 29, 79, 63, 68, 81, 109, 89, 32, 64,...   \n",
       "3    [[0, 106, 29, 79, 63, 68, 81, 109, 89, 32, 64,...   \n",
       "4    [[0, 193, 95, 191, 53, 198, 167, 136, 88, 91, ...   \n",
       "..                                                 ...   \n",
       "115  [[0, 204, 191, 33, 157, 132, 8, 172, 129, 89, ...   \n",
       "116  [[0, 171, 166, 200, 26, 78, 77, 9, 3, 137, 136...   \n",
       "117  [[0, 171, 166, 200, 26, 78, 77, 9, 3, 136, 130...   \n",
       "118  [[0, 171, 166, 200, 26, 78, 77, 9, 3, 137, 136...   \n",
       "119  [[0, 171, 166, 200, 26, 78, 77, 9, 3, 137, 136...   \n",
       "\n",
       "                                          drone_routes  \\\n",
       "0                                                  NaN   \n",
       "1    [[[83, 78, 169], [62, 159, 129], [132, 34, 191...   \n",
       "2                                                  NaN   \n",
       "3    [[[83, 78, 169], [62, 159, 129], [26, 76, 87],...   \n",
       "4                                                  NaN   \n",
       "..                                                 ...   \n",
       "115  [[[175, 123, 141], [138, 93, 135], [148, 149, ...   \n",
       "116                                                NaN   \n",
       "117  [[[152, 111, 157], [125, 196, 60], [172, 198, ...   \n",
       "118                                                NaN   \n",
       "119  [[[152, 111, 157], [125, 196, 60], [172, 198, ...   \n",
       "\n",
       "                                          robot_routes distances       time  \\\n",
       "0                                                  NaN   [71461]  [491.461]   \n",
       "1                                                  NaN   [66541]  [468.401]   \n",
       "2    [[[93, 8, 165, 146, 113, 197, 168, 67, 11, 103...   [60636]  [391.501]   \n",
       "3    [[[93, 8, 165, 146, 113, 197, 168, 67, 11, 103...   [57243]  [401.251]   \n",
       "4                                                  NaN   [70735]  [490.735]   \n",
       "..                                                 ...       ...        ...   \n",
       "115  [[[118, 170, 68, 102, 161, 144, 12, 177, 179, ...   [59110]  [363.884]   \n",
       "116                                                NaN   [71259]  [491.259]   \n",
       "117                                                NaN   [65713]  [467.939]   \n",
       "118  [[[48, 46, 54, 103, 31, 149, 88, 182, 162, 179...   [63132]  [367.857]   \n",
       "119  [[[48, 46, 54, 103, 31, 149, 88, 182, 162, 179...   [59820]  [380.186]   \n",
       "\n",
       "      waiting dispatch  total_distance  travel_time  time_complexity  \\\n",
       "0         [0]        0           71461      491.461           3.4456   \n",
       "1     [15.86]     [34]           66541      468.401           3.9492   \n",
       "2    [54.865]     [16]           60636      391.501           3.3019   \n",
       "3    [68.008]     [36]           57243      401.251           4.0676   \n",
       "4         [0]        0           70735      490.735           6.2699   \n",
       "..        ...      ...             ...          ...              ...   \n",
       "115  [10.774]     [36]           59110      363.884           4.3262   \n",
       "116       [0]        0           71259      491.259           4.8988   \n",
       "117  [16.226]     [34]           65713      467.939           4.4685   \n",
       "118  [10.725]     [14]           63132      367.857           4.3743   \n",
       "119  [26.366]     [36]           59820      380.186           4.6138   \n",
       "\n",
       "     space_complexity  \n",
       "0              4.9473  \n",
       "1              9.0293  \n",
       "2             23.9941  \n",
       "3             18.9150  \n",
       "4              4.4912  \n",
       "..                ...  \n",
       "115           28.9287  \n",
       "116            4.3809  \n",
       "117            6.1289  \n",
       "118           23.4141  \n",
       "119           22.6348  \n",
       "\n",
       "[120 rows x 18 columns]"
      ]
     },
     "execution_count": 202,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_result = pd.DataFrame(result)\n",
    "df_result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 203,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: xlabel='id', ylabel='travel_time'>"
      ]
     },
     "execution_count": 203,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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LW0KVw8sdL6ylpt60npVmIjPNTJbNRJbNzInD8pp8IKnA9AmFVFW78PiCeP1BPL4gHl8AVYXTxjXttlqyqoS5pw3EH1SRJYl+vdIY3CeDwX0zGJCfQYpZ3/xbwslF/LjzMKXldZSW7+CdL0qZMro3Z5zYJ8JtBM37d/ccrOWD1Xv4ZnMFSv3DpmeGhUM1LmZNLua1Jt5Q1m0/xFcbD/LVxoOcMKgn551cREFOatRrbYiqqrz/1W4Wfa71y8kje3Hp2YPRyfHH6/RIt3DTL05g0ee7+GD1HrburcGcYuLdlTsjZ4udXMTMk4v57If9VDo82FIMnDm2D6eNziel3uJ0tBXC5QmQYm5shSjomcqFpw1g7qn92bKnmq82lLNtn51hRdnc99K3Udv57spdnH/aAP7yr2+otHvw+oME6i1nNquRp285s9nYlbmnDeCZd7dhNevpkW6hR7qZHhlmstK0B2lnPMxcngDLVu/mozV78dVXgx4zJIesVAMXTB2IJEtNCohYiObmbIlYxEtztMbyJEsSeVkp5GWlIMVgdcpMM/HzMwY1KeSaavusycWcO7mYPz22kn0VdazdUsHsSUWcMaag3VI8JNvDsCnUetf0os93sbeijnSbpclUGLMnF+P1Bbjs7CGN1gWCCh5fkKz05l8qM9JMjB7Uk4H56QSCCv6gQjCokmkzt+hi9XiDzD65uMnfWUv3WqrFwC/OHMT08YV8sHoPn64rY+d+Bw+98QNFvWxcdMbA+mdSy79xVVWpdfs5cNhJZa2XsycVJ1V8mRA/HUgsCfPSrUaqar04nD5q6nw0vDVsViOnjyts0az99+fXNjJrF+alMWpI826rOref3194PHlZFszGxrdCS4O63e7i0rMH8+E3eymvcrHs6z0s/2YvE4bncda4PvTNs0X17/q9fn7cWckHq3ezsbQ6fL5h/TI5+6S+DO+XhV6v44LTBiA1ce49ZTWMH57L6o0H+a7eTDt2aA7nnlxEr2xr+JgNTbNBReHVj7ez4tt9AMyYUMj5pxS3i19br5P5yWkDGNwng/R0C+9+vjNicHS6/bz20TZUFa48dwQ7d1cx6bheUa1NISuEEgiQkWGlpsaJ3x99MJNliWH9shjWL4ugota/aTYTf1LnQ5IknJ5AxLosmwm7s6U3Uh87yuyN3kh1skSWzcQffnYCP6ze0+i622PKdiCo8On3Zbz7RSl19W0cWJDOT04bQP/8dO1cMYjGjiAet1m0Y7TW8hSr1akli1dT/ebz+PnltMG88vE2SstreeN/O/jsh/38bOoARvaPnOHYGheIqqrsP+xi6MDm8yt11sOwubZv21vDws92sn2fHQCLSUfZwVounDoQuZVCW6+TSbXILX5nXm+A2RP7RW1nS2I3lgSssdxrmWkmfnbGQKaP78uy1Xv49PsySg44kPU63lyxPepvXFVVJh7Xmzc/3sqBKhcHDjvD40xhXhrjj+udFPFlIYT46UBiGZx8/gC3/WocVQ4PVQ4vVbUequv/NRn12FsI5LQ7ffTIsKAoKiaDDrNRh8moI8tmbtFtlZ5qpKiXrcnBpaVBXULi1FH5TD6+Nz/sOMwHq/ewfZ+dVT8eoPRgLff9bjLvft7Y+jFrcn9e/98O9lXUIUsSY4fmcPa4SPdVS+fOSDVx9azhzJjQj3dWlbB2SwXfbK5gzZYKxg/L48LT+5PXIy3CNLu9Pq4J4GdTB3Lm2D5xfKvNM2pgT9IzLDz4yndR17/3RQk/PXMQhT2sMTwkIv9tCb1OxmY1tmgJuGLGUHSyhMmgw2jQYTLIGPS6FgNvM9NMTDouj355aRyucXPI7qHS7iGoqHj9CgP7ZHLnc2uiti2ULPDHbRXkZaVgi+JCiW5O97NuSwXPf7CFimo3AHlZKVw4pT+jBvaIEK6tEY3tTbxus6NpreWprVanhm2P1m8DCtKZf+kYvlh/gIWf7eRglYuH31zPyP7ZXDR1IPk9U2NygXh8ATaVVrN+52HW76wkPdXUYn6lmlov328/xKCC9GZj8Toiq3bJfjuLPt/F+p2VgBbjN/XEAqaPLyTVYmiT0I73O2sPsXv08Vq619JTTVw0dSDTxxfy6Q/7GTWoJw+/9n3UbUPehB92Vka8jPdIN5OXldLi+NLRmfOPRoifDiaWGz3daiTdaqSoV+S+kiSRbostmDLaDd+c2yrWH0osg7osSYwe2JPRA3uys8zOB6v3cPakIt75rGnrx2Uzh/H1D/uZNrYPPZqYIRXLufN7WPnteSPYW1HH4pW7+H77YfYeqiOnRxrvrNzFe18cEV4zJxVxz/+dzHebDjCiKLvZ646XRNYGi2Vw9HgDFPSM7h6MZd8zTowUjIqiUlPnxeUNtmh1qq718uqK7ewuryXdaqRPTmr4b0BBBsV9MxuZ02dOKmLW5GKMK7ZjSzFw7uRiTjm+V7NuytaKxvYkHrdZW2gPq1OIpvpNliQmH9+bEwfn8N6XpXy0di/rd1Zid/q459rJvPPZjogXnLB1dn8NazZVsH7nYbburQm7WEELGG/p5Swtxcjzy7bg8vgZ2b8H44flcvyA7HAcS0dk1Z51cjHnnlLMf9/fHH45O+X4XsyaVBThzm+L0G7Ld9YeYjcebFYjc+qfGc1OgnH7mXNKMSaDTO9sK7lZKZjqrdvNBfa3Vri1B0L8dDBtudHbqvTb84cS66DePz+da+eOJD3D0uQbwntflPDimWfRPzct5qDSls7dJyeV380dSWm5g5QUE0tW7mokvF7/eBuSBLNOLsbbQbEEia4N1pbvPJ59ZVkiy2YmW5JatDplpJrQ62UkwO70YS+pYkNJFQC3XD4uqjk99PmGn5+AQaJNQfXHKu1ldWqJFLOen5w+gFNG9ea1FduZdUp/Fn+6I6oLJDTz6NUV28PrcjIsjOyfzcgB2Qzuk9l8TOHkYvYfrsOWYsDh9PHdtkN8t+0QFpOeEwf35PQT8hk5OLfds2q/9pHmvrl0xjA+Xr2b8yYXkZuZ0uRx4hXa8X5n7Sl2W4uiqKSnND+2ZaQamTIqP+q1JEq4NYWkJnNShQQSDCpUVTkbLdfrZTIzrVRXOwkEWnejtSX9/ML/7WjyhmlpurveqMdi1kf8UDpyKqlOJyMZdPxywYdNbvPigrNR/O3fBkmSSM+wcMmCD5v8gb644CzsNe4Oe8swW4ws+aIk6qD+s2mDmTmpKCbxFe+91pbvvC37xnrdXl+QfYfr2Huwjr0VdVTVepl/xUlc9vfl7fKdteU32p1pTb9JkoQt3cIvb2v6d/bcX6dx7wtr6N/bxsj+2eEg7RCxjm37Kur4alM5qzcdpKp+Zuotl49jx96aqEHHP5s2mOkTCjlU6cTbYCKI1x/E6wuiqHDmhH7Ntv2FW8/CYW/5fkvkvZaI3EhtHdsaji8N3YXt+TzKyrKiiyEoX7xGdSLxmMTbqvQ7662wIYm0fiTS7RQi0W84bfnO27JvrNdtMuro3zud/r21QGWdTsbtbd6c3tnBkILmkWWpRTenxxfgd3NHxj3zKDyzMSeVC3O0mY3b99bww87KZmNPQlm1Fzy7psms2mOG5zXbdpcn+e+3znaxQvvMbExUXN7RCPHTBWgPAdOZP5T2DsxrDYl2O0FiTdMNact33plCPRm+M0HriO07M2D3BqLsfYTWjG2yJDG4bybDirJbFMt2p48smwl/IIjRoMNs0CaCmA2xTQYR91t02mtsS2RcXgghfroQiVD68ZIo60cihVdDEmFxSwYSNWVb0LkkYuZRiFiEV5bNxN8uHdvkMdpjMkh35VgZ24T4EXQIsSbr6wgS7XZqSFcSrO1JIqZsCzqXZH/BSca2H0t09bFNBDw3QUcEPHdXDAa50/27iQj0bm+6273WXt9Zd+u39iKefkvU76ytE0Haq+3iXouPjuw3EfAsSBoS4d89Vkyz3QnxnXU9EvWdJSqrtuDYQYgfwTFNVzfNdkfEd9b1SMR3lqis2oJjAyF+BAKBQNBlEeJFEA/tU55XIBAIBAKBoIsgxI9AIBAIBIJuhRA/AoFAIBAIuhVC/AgEAoFAIOhWCPEjEAgEAoGgWyHEj0AgEAgEgm6FED8CgUAgEAi6FUL8CAQCgUAg6FYI8SMQCAQCgaBbkVTip6SkhNGjR7No0aLwso0bN3LJJZcwevRopkyZwgMPPIDP5wuvVxSFRx99lMmTJzNq1Ciuuuoq9u7dm4jmCwQCgUAg6AIkjfjx+/3ccMMNuFyu8LLq6mp+9atfUVxczOLFi7n99ttZtGgRDz/8cHibf/3rX7zyyivcfvvtvPbaayiKwpVXXhkhkAQCgUAgEAhCJI34eeyxx0hNTY1Y9u2331JTU8Of/vQnCgsLmTx5MrNmzWLlypUA+Hw+nnnmGebNm8eUKVMYMmQIDz30EOXl5SxfvjwRlyEQCAQCgSDJSQrxs2bNGl5//XXuueeeiOVZWVkAvPrqqwSDQfbt28dnn33G8ccfD8CWLVtwOp1MmDAhvI/NZmPYsGGsWbOm8y5AIBAIBAJBlyHhVd0dDgc33ngj8+fPp1evXhHrTjjhBK655hoeeeQRHnroIYLBIOPHj+dvf/sbAOXl5QCN9svJyQmvawt6fWNtqNPJEf8KWkb0WXyIfosP0W/xIfqt9Yg+i49k6LeEi58FCxYwevRoZs2a1WhdXV0du3bt4he/+AWzZ89m79693H333fz1r3/l3nvvxe12A2A0GiP2M5lM2O32NrVLliUyM61NrrfZLG06fndE9Fl8iH6LD9Fv8SH6rfWIPouPRPZbQsXP4sWLWbt2LUuWLIm6/v7778dut/Poo48CMHz4cNLT07nsssu47LLLMJvNgBb7E/o/gNfrxWJpW6cqiorD4Wq0XKeTsdksOBxugkGlTefoLog+iw/Rb/Eh+i0+RL+1HtFn8dGR/WazWWKyKCVU/CxcuJDKykqmTJkSsfzWW29l6dKllJeXN1oXivcpLS0lPz8fgIqKCvr27RvepqKigsGDB7e5fYFA019KMKg0u17QGNFn8SH6LT5Ev8WH6LfWI/osPhLZbwkVPw888AAejydi2bRp05g3bx6zZ8/m5ptvZuvWrRHrQ5+LioooLi4mNTWV1atXh8WPw+Fg06ZNXHzxxZ1zEQKBQCAQCLoUCRU/ubm5UZdnZ2eTm5vLZZddxlVXXcXDDz/M+eefT1lZGbfddlt4WjvAxRdfzAMPPEBWVhb5+fncf//95OXlMW3atM68FIFAIBAIBF2EhAc8N8fkyZN56qmn+Oc//8nzzz9PZmYmZ555Jtddd114m3nz5hEIBJg/fz4ej4exY8fy9NNPYzAYEthygUAgEAgEyYqkqqqa6EYkI8GgQlWVs9FyvV4mM9NKdbVT+HhjRPRZfIh+iw/Rb/Eh+q31iD6Lj47st6wsa0wBzyI5gUAgEAgEgm6FED8CgUAgEAi6FUL8CAQCgUAg6FYI8SMQCAQCgaBbIcSPQCAQCASCboUQPwKBQNBOSJKETicjSVKimyIQCJohqfP8CASJRpIkZFlCUVREVghBU+h0MikmMJqMKB4nstmKz+vD5UXUfBIIkhAhfgSCKIiHmSBWdDqZ9DQD9i8XUb52afh+sY2ZQfrEOdhr/eKeEQiSDCF+BElPZ1tfxMNM0BpSTGD/chE1q94ML1M8TmpWvaGtHzOTWleiWic4VhFW6bYhYn4ESYtOJ5OWIpOVYcJm9JOVYSItRY4pe2dbaPgwUzxalu/Qw8z+5dukmDr09IIuhCRJGE1GHGuXRl3vWPs+RpNRxAAJ2g2dTibVLJOVbiJV9mv/mjp+XDzWEJYfQVKSKOtL6GFW3szDLGPS+Uhur3jbEiBJEHTXhkXy0SgeJ4rXhSzrCQaT+34J6TOh05IXnU4m3Wpg38JFHHhvKUGnE53VSq9ZMyg4fw52p7BKx4qQioKkJFHWF1mWtAdWcw8zjxNZ7vgnRFsfRmLmUcehqiqBPetwvncvOlMKstkadTvZbEU2paAoySt8QhZWW6qRoNOOLdXYKRZWQeuxGGDfwkXse/1Ngk5tjAo6nex77Q32LXobizBnxIzoKkHSkUjri6Ko2gPLbI0qgGSzFdloxrX83+iKT0LXewiS1PRDIh6/fMNga+1hlNKqYOv2CNYW8QTRUVWVYNkmvGsXoVTsBMC9ewO2MdMjYn5C2Macg3vXD/gOV6IfMCHphKiIb2sbnWktkyQJk9nIgfeij4sHlrxPnwvOx+kTVulYEOJHkHTEZH3pIFeCoih4KvZgG3MONavearTeNuYc3CXr8W3+DDZ/hmTLwTDkFAyDTkZOyQhvF68AaevDqD32786z3JoTfYEDW/GtXUTwwFZtgc6IYfhU3Kl9yZw4EpBwrH2/QZ9PJ33cDPY/fwv+yjL0u7/HfPKlSObUzr+wJhDB2vHR1heUeJBliYDTGbb4HE3Q6STg7Bou1mRAiB9BTHSmJSAm64spBcXtbfdz+9YuonLPd/S+5Ha0h1ljAVG1pxTD0NPw7/gK1VGB75u38K15G33hKAxDT8XYd2TcAqStD6O27H+sWAHieRtvTvT5DmzHu2YRwbKN2sayHsOw0zCOmoGckoEK2Gv9pIyZScak8zVhbkrB5/FR4wwiFY2DqncI7FqDs3w75ilXoi8Y0e7X3VqSKb6tK1kaE/U7URQVfZoVndUaVQDprFb01hQUe/uPi8ciQvwImiURlgB/6fe40y3NWl98LieqqmvX83q/ewff90sAOLzhG9LHzCJj0tyIh5m91g+2XpgnX4pp/EUEdq7Gt+UzlIqdBEq/JVD6LbaL5mPfuLVpAXLiDOxVDlR3LarHgerW/i8pXoynzGn+YTThXJxv3IjisoMKoIKqgKoiW1LJvubx5vefeB7+rxahykYkiw3JnKb9a0kjLTuzS1sB4n0bb/phNp30cTPZv/IZgpVlIOkwDJmMcfQs5NTsiGMEgwq1LpDcXmRZjxIWDBKmE85FX3Acnv/9G8VejnvpAxiGT8V00k+Q9ImbOphIC2uIrmhpTJS1TFVVvB4fvWbNYN9rbzRa32vWDLxuX9KLx2RBiJ9OpCu93UDnv+Goqor/xw/xfv06geze9L70ThpbX84hfcx0Dix8EMOEi5EzerXLub3rluJb+zYAppN+ilw8nlqXEuVhdgTJYNJcXkNOIVi1F/+WzwnuXY+lz1AOLX4o6nlCAsa9cD6KyxGxztCzL8ETT2v2YRR0OdAZjCg+d6P1OksaQZe9+f2ddoK7vsF/aE/EOjnFRs//e6LdrABdKTdT0w+zNwGVrNMupnL9F5hOmI1sy2m2HaqqRhUKupxiUubehnf1G/g3rsC/cQXBsk2YT7saXc+i8Had2W8Bpx05LTshFlbompbGRFvL3H4oOH8OoMX4hGd7zTgnPNsrVrra86i9EeKnE+iKbzfQuW84qhLAu+pF/Fs+0xb0HEiNU8F6tPXFWceBxY/g27sRf8WdWM75A7qc/m06t+/H5fi+0a7JOOZ8jMefc6RdTTzMjkaX1QfdxF8gcxFBr6tlAWPNQA0qSJa0sAVGTs9BZ81s9mGkS83EdMa1GIOK5tcJ/SEh6XToUrOa39+agVxwHPq0PFRPrWZ18tSiS82MQTjV4F/7PorJhq5nEXJ2XyS9MbIfEnSvN3+vqliOO53qkk2o3jrwulC9TlSvEwmF7Fm/buZhtoy+1z1NSvawNj8gJL0J86RL0Pcdheezp1FqDuBafAfGE8/FcuIsrBZdp/VbYO96PJ/+F+vMa5q1sHrrHKiqMcoR2k5XjDeKyVrmrkOSDHSYnpAhd8pJFMw5F7/dgSHdRs26H6jdthXyi1vcPRmeR8mQVkGInw6mK77dQOe+4aieOtwf/5Pg/s0gSZjGX4RhxDQUVYpifdFjmHwFAedDKIdKcC25F8uZv0Xfd1Rc5/Zt+gTvV68AYDxhNqYTZrftWiQ9OoupRQFjPm8BRJkl5vP5sY2ZEX4ANMQ2ZgY+rw8pLYemxgyf19f8/j4/xrEXRms5ulRL8+22pOHd/NkRi5WkQ87KR9ezH3LPYoz5Q0jv2xf7l2+36V5v7Rtpy/fqUjImnIfvi+ejW9ucNZ3q+tH3OQ7rBXfgWfU8gV1rUEtWk3HKbOzfLOnwMUIN+vGufhP/huUA1Hz7MXlz/wjIRwVraxbW/a/eju646RiKx7bL+UMk2oISL0G/FzmtpXhEC8537sMwcjr6XoPb9fwhwVj12ZtUbrdhzMxAJ9VQW+ogbWA+g/56Gw63HwzmqDML2/N5lIiZrO2JED8dTFd8u4H65G0uR4e/4Sg15bg+fAjVfhAMZixTf9NIyBxtfZEtNlJm3oT7438R3Lse94ePYp58GYYhp7Tq3P4tn+Nd9QIAxuOnYzxxTvwX0qCtLQoQry+q8AFweSF9otaOyIfRkcGpOeLfX2qh3dPxOmrQDz2d4KESlEMlqG4HSuUelMo9sOVzMi68CfuXayOsCK2511vzRqoGAwQrdhLctwHJWUnwzIubt1q5azH0HUnA6UAyWcN/utRMdKnNW9s6wvUjmVMxT/0tgcKvSO+Zjf2b9+Lut1gJ1uzHs+JJ7fsCDMOnYjjpp9jrguFgbdXnQjKm4HO5KP/wOfwHS/Af/CfKqJkYx5yPJLdT7p/acoKG9C6VHFKpPYz7o8dJOe2nzVjLpuMu/ZHA7h8I7P4BXZ+RmMZdiC67T7u0ISQYFT8EHA6CdQ6yh0EtULujDMnnw/XGn1F8HiRLOlJKOnL9v5IlnewTTsX+5Rdteh4laiZreyPETwfSVd9uFGc1ntWvkTlnXotvOK4lD6IfPg197yGtPk9g/2bcHz0OXidSajaWs3+PLiu2QUIymLGcNQ/P588S2PYFns+fQXHVYBw9K6ZcKv7tX+L5/FkADCPOxDjuwnbLwdIWARMMKhEzh8IPo/pg65YGh6P3PzpYu7n9Y2m36cTzAE3kqc6qI0LIcRBLv5EcWvJ41GOHg61XL4G0nuiy+iClZYdzJLU0MNY4fPirygju20hg3wZturnfA2jxSrqU9BbdfaZTr8IY5Xfm87ZsbeuI36ckSRgHTcKSYeLQu49G3aY9xghVVfFv/Rzvly9DwIdkSsU85Qr0haOBI8HaBr+PjIx0amqc+P0yhkmXougt+H/8EN+69whW7sFy+q+RTNETOsbUFq9Tmzm3ey1Zv/1Xi/m0grW1oEt8PZnAvg14VjyJ6q2jetUiev3iVhpby7R7tbrisDYbdMtnBPeux7X3R/QDxmMaM6dRzFgs1hOlphz/zq+RqvcQPOdKTRjWDyGyHgwpYLCC3wkHP/oInTUDxbUHtfYQau0hQr94OcWG6fQLONjshIg5BLd+AylZyLYcJENk33dMbF1iDAFC/HQgsfmHa5F8PlRD/ANKe+Lf9Q2elc+D14m79Mdmkrdpbzj+ku/wl3yHrvdQjGPmoM8b1GjbaP5d35bP8K58AdQgck5/LNPmIaekt6qtkqzHfOqV+FIy8K17H9/aRaguO6aJv2j2DdW/6xs8n/4HUDEMPQ3ThJ+3a/K5tgiQ0P6NH0axvxE1PfOo/dotSRJSarY266loDDqdjOLztBxsveOLI8HWBjNyVgG6rAJ6TDqvmTdSFXP+IOxv3BlxTMmchi5/OPqC4fg8nrgFTFutbW0h5jEiEETVmVt9fNXr1F4QStYCoMsfjnnKlcjWzMbbqpH/SrIO84SfoetRiOfzZwnuXY/z7b9jmTYPXVZ+69qhKvi3rsT3zVuonloAPAd3t5gcsu7DpzFPvhx9wfBWna+9UFUV3w/v41uzUJtR2aMfhim/xu5UmnxBUY1pmCdfinHkWXjXLCKw6xsCO74isOsbDEOmYDxhFoa0rGatJ0pdFYFdq/Hv+Brl8G7gKJFfrd0vskFrZ0pPsDvh0Mqv6fO3WzG6HKguO4rbjuqyo7rt6PWGFkuxaHF9C8O/UcmSromg9BxkWw7ZJ5yO/cvPm46tG3kGNftLwO9G9dX/+d3IqBinzE0qQ4AQPx1IrPlqap++ASmjAMPACej7nYhktEQ9XkdG56teJ54vXiKw4yutbT0KcRmzyZp4PI2Tt9W/4Rw8hGHY6dobzv7NuN/djC5/OKYxc9DlDoju3/V4qV6zDO+XrwGg7z8e86m/ahQ4GyuSJGEadyFSSgbeL1/Bv2kFqtuO+bSrkfTGRn3mL/0Oz4qnQFUxDJ6M6eRLOiTrbrwCpCFHP4xaS6zB2g2Jt92x3Os6awZS7kBkBZTq/eD3oBzcAbUVmGZe1cwb6VL6TjgP2ZqJlNGrXvCMQM7uE7YcuQJyu1nbWitW20LsY8T/IfcoQj9wIvq+x0f9vRx9rwcObMXzyVOoziqQdJjGzcUw8uxmM5JHwzBwInJmb9zLH0N1HMT1zu2Yp1yJoWhMTPsHK3bh+eJFlEMl2jVl9sY06RI81gLSJxYRdXwZP5sDr9+NWnsY99L7MQw5BdP4i5CMKa1qe1tQfW48n/6XQOm3ABgGn4Jp0sVIemNMLyhyeh6WM35L8PB0vN+8RXDfBvybVkDlTnpc/Hfsq4+O8ZpO+kmzKX//v3i3fEF9LguQZHQFwzH0Hx+2UtYt0kR+SPyYs6G2TI9n/wHcu3aTMmgw2HJomAxEkiR01hbiEa3pqOZ0MFnB60R12wm67XBwu2Y5Oq05y5EWW+f95F/RY+vGTk0qN6cQPx1Iy/Ef03GXbUdx2sFp15Ko6Z5HXzgK/YAJ6PuMRNLpOzw6P7BvI57P/ovqrAZJwjhqJsYTzgWdvtmHgmqyYT75lxhHzcD3/RL8W1YSLNuIq2wjphGnkXfOldi/WnzUD/wccsZNZ//WlUhF4zCOnt0u4sM44kwkSzqe//2bQMla/CYz2dOuwGgxh8/trank8PeLQQ2iHzAB0+TLW/0gaC3xCJBkoLXtjinWyefHNPESTGiz+5SagyhVe5H9zhiKg7pJ+8X9KE0MWe3hLmyrWI2HmMaIfdtQnDUozu8J7P4ejBYMxePQD5yILm8ger2+0fjgObSXyq9eRHVWIdlysUz9TcSU+tai69GPlDm34lnxBMH9m/F89DjK6FkYx8xBkuSoL2aK24Hvm7fwb/1cO4jBgmnMeRiGT0WS9c2LTqeC8YzfoX7zppYaYMvnBPb+iHnypXFPbmgNweoyPMsfQ7GXg6zHNOlijEOnNNoulhcUXY9+pEy/gcD+zXhXv0nWKRdiX/1ulBgvLbVCxohJHNyyCl3eIPQDxqMvGoNssQHg8msi//DXm6B0A7JBEy0ZY2agZhyiYsX/sH/+qSZ+GrU1lt9oAMs512vbe50ojgrtz34QHUrLliN3LYa8gfhrq5GMFu1F3mBBTs1ocSZrR6ZViIakJlOwSRIRDCpUVTX+kvR6mcxMK9XVTgKB2OosaT7St5t8I/VXl+Pf8RWB7V9pP7YQJiuWkdPIOXUu9q/fiZptuC0zaNSAV5v5sfFjbRtbLpbTrkKXOyCm/Y9GqT2E77sl+LetIveCP+E9sDNqUGDGyRdgGXYqdaS12O7WEti/mcCat+j9s1uwr12KY+2yRjNYDn76BvoxFyLJ7Zsksb1p7b2WaGK516Pdq5IkkZVhYs8jVzQ5MPa97mmqamITJAaDTEaGtdXuwkQRS7/5Du0lsP0L/Du+1iw59Rj7jqDXhTdiX70kaj6sgysXoz/unCatyQ2J5X5TlaCWq+jHDwEwjTid7NMvwWixHHkx83ixb/wK5+fPQ30+Kv2gSZjGXRhRAqYhLZUV8Xz2DKrjoHasARMwT/xFuExIWy3ijazDu77B8+nTEPAiWbOwnHktupzoU8jj+Y1mZ5rY88iVTd/r8/7L4f3lSCmNXZOg3S+HX3uRQx9+RO/ZMyi89BJ8Hh+VW3ZSevttSAYDxQ88jM7aOJQi3t9oqJ/a8jtNS5FxrX0vqvDKOPkn9TE/bf+9ZmVZYyrKK8RPE7SX+IGjouMbvN24fJGWG1VVUQ7v1oTQztWorhpyL7ypGRHR8g3TlNWo9sA+nB8+hlJzAADDsNMxnfTTRgFu8aDWHaZHQW/2PHpVuzzMWkuqwYf7h+VNCq+UE2dR607+276riR+I/V4/mvYcGI/lflNVheCBrfi3fUmgZA25513XzPhwISljZnVIv/m3f0lw44f0/vmtTb5k7H/xrwTRY550Mbq8ga3rkKNQA168a9/WRJeqIllsWKf+GtuA4+K2iEcbGz0Ve6h89xH8lWXoeg/FPPWasNUlGvG8DNuMfvY8ckWT2/T9/TM4vPpmr+HAU/+ids035P7s52SccZY2AUFV2b3gr/jK9tHz5xeTefoZLV93K36j0LbfaVuEV2uIVfwIt1cnEKtJXZIkdD37oevZD/Wkn6JW7MBSNKLFGTSBdR9Dak/kzPyIH2pzafuzxpyDRyejpmRgPvVX6PuMbLfr1afnoHjdCfHvSpKEKdXGwbXLoq53rF1GxqQLkDzJNcPuWCFe91Eig46TgdjHCBl976Hoew+FUy7Bkp3WzPiwlIxJczskiNQwcCKZQ0/EvnZpFPeN9rnHnD9Ri61dpsdLehPm8RdhKB6L57On0ckS2QOGYl/7LuURwqutBYDPofclt3NozUfIQ89od+twe9UtDDi0mBop1Rb+biVJIv2UUzn06svYP/+MjNOmRg0paIuLN5EzWdsbIX46kdbEUUiyjD5/SIsiIui0E9j4cYPofJsmgjLz6TFxZhMzaDTfcvb031Inpbd7lelEFiZNhnpFgtbHDCUy6DiZaE2/6QxmFE/z2cQ79CUjLb3FlwxnO1t3dTn9STn/NtJUexPCq37W0YjTqNm/W8unJUlabJ8khT+n9uqN/cslUcbGtwCJjLGxW8xaQ6x5wFrqs2CtJn70tkirlG38RA6/+Tq+fXvxlpZgLmo643O8EyISOZO1PRHiJ4mJdQYNGQVIHreW18HtIOh2oNaUYZp+eTOR+drg5OoA11N7/cDjIZHCS9A2EhV03FXpri8Zst6IKaOAg680JbxCs46eaDTrCLQp4zn/90Tzs5Y6yGIG7WPlDDq0dAG6tMi4SZ3VSuqJY6ld/RX2lZ81K37iJRlmsrYHQvwkMbHOoDGfdrW2vd+LUrMfpWofcsAVwwyajrOAJMqNkUjhJWgfuuoMuc6mu75kxCK8gu5aDL0G4q/cj6oq2lO2/l99Vq+Ws9d34NjYVuuJGgwSdNYBYMzMRJKkiO84/ZRTqV39FY7Vq+n5k58hm1ufHyoWuvrvVIifJKc1IkIymND1LELXsyimnA4daQFJpH+3u8ePCLoP3fElI1aLuOmMeVEzekuShC41cWMjtNF64nZqYk6SMPS0kGo24/H68HtUgkEFy6DBGHJz8R88SO2a1aRPPrXDrqMrI8RPkhPvW0IyWEAS5d8V8SOC7kIi7/WuKrySYWxs2JbWWE90OhkpqNWAcJskfv3eX7AaUjhn0BTOHXIWTof2naeffCqHF76BfeVnQvw0gRA/XYCuPoMmEf5dET8i6C4k6l7vysIrWcbG1mIwS3yy4RN6AE6TNpPL6Xfx1kYtfumc4qkEnWCbOInDixfi2bUL7769mArap7DqsYQQP10IMYOm9XR1v7RAECuJuNe7qvDqimOjJEmYTUZ+3PEdpwFuc2QKgWXbPmXO0HPwujzo09NJPX4Udd99i33l5+T87BeJaXQS07G5/QUJRxucFKpqvDi8eqpqvNS6laT8cQsEgq6JJryUTrWutnVs62pjoyxLOH0udE4PAK6jxI/T78LldyPLmkUo/RTN3eX46ksUv69zG9sFEOKnm5CIwUkgEAg6mraObV1lbFQUFasxBZtPS7zoMkU+vq2GFFIMFhRFu46UYSPQZ2WjuJzUffdtp7c32RHiRyAQCASCJEdVVTxeHwONPQFwWyIf3+cMmoKnQaC2JMuknzwZAPvnn3VuY7sASSV+SkpKGD16NIsWLQovq6io4I9//CNjxozhpJNO4vrrr6eqqipiv5dffpmpU6cycuRIfv7zn7Np06bObrpAIBAIBB2K36PSW9ISGwZTtPw9VkMKc4dN59whZ+H3RFqvbCdPBknCvXULvoPljY7XnUka8eP3+7nhhhtwuVzhZT6fj1/96lfs37+fF154gX//+99s2bKFm266KbzN22+/zX333cd1113HokWLKCgo4PLLL28kkAQCgUAg6MoEgwreKjsAl516GY/PvIMnZt/FcblDw9PcG2LIyiZl+HEA2Fd+3untTWaSRvw89thjpKZG1ph67733KCsr4/HHH2fYsGEcf/zx/PnPf6akpIS6Oi3D5ZNPPsnFF1/M7NmzGTBgAHfddRcWi4U333wz2mkEAoFAIOiyBBya+Hl4w6vcu/Jf/N9787l/5RP4A4Go24cDn79chdrENt2RpJjqvmbNGl5//XUWL17MlClTwstXrVrF+PHj6dGjR3jZ5MmT+fjjjwGorKyktLSUCRMmhNfr9XrGjBnDmjVr+PWvf92mdun1jbWhTidH/CtoGdFn8SH6LT5Ev8WH6LfW09l9pqoqwfqK7odlL966w4CEN+jloKeCPmm9G+2TccJoKmzpBB123BvXYztxTKe0tTmS4V5LuPhxOBzceOONzJ8/n169ekWsKykpYcyYMfzzn/9k8eLFBAIBTj75ZP70pz9hs9koL9d8mEfvl5OTw5YtW9rULlmWyMy0NrneZrO06fjdEdFn8SH6LT5Ev8WH6LfW01l9FnC5Uf1aAkaXWSbbkk6v1J6sK9/EXvceRvYdGHW/vDNOo2zRYpxfrqTwjOTJ+JzIey3h4mfBggWMHj2aWbNmNVpXV1fH4sWLmTBhAg8++CB2u527776b3/72t7z44ou43W4AjEZjxH4mkwmvt211WRRFxeFwNVqu08nYbBYcDnfS5oNINkSfxYfot/gQ/RYfot9aT2f3ma/iIACq0UBAL5Gqt1KU1o915ZtYV7aZiTnjo+5nHjcRFi2m+rt1VOzYjSG7R9TtOouO7DebzRKTRSmh4mfx4sWsXbuWJUuWRF2v1+tJSUnhwQcfxGAwAJCens6FF17Ijz/+iLm+Wq3PF5nAyev1YrG0XVEGAk1/KcGg0ux6QWNEn8WH6Lf4EP0WH6LfWk9n9Zm3qkY7X/1Mr1S9lQHpxQBsq96Fzx9AlqKEa/TIwTJ4CO6tW6j67HOyZ5/X4W2NhUTeawl17i5cuJDKykqmTJnC6NGjGT16NAC33norV155JXl5eRQVFYWFD8DAgZpZb9++fWF3V0VFRcRxKyoqyM3N7aSrEAgEAoGg4wnWavE+/hTN25FqTKVPaj5mnQl3wM2+uv1N7hsKfLav+hxVEeI2oZafBx54AI/HE7Fs2rRpzJs3j9mzZ7Nw4UJeeOEFPB5P2Mqzbds2AAoLC8nOzqaoqIjVq1eHg54DgQBr167l5z//eedejEAgEAgEHUjAUQuAz2IAFNKMqehkHf0zithYuYVt1Tvpm1YQdd/UE05ETrESqKrCtWkD1hEjO7HlyUdCLT+5ubkUFhZG/AFkZ2eTm5vLRRddhE6n4/rrr2f79u18++23zJ8/n5NOOonhw4cD8Ktf/Ypnn32Wt99+mx07dnDzzTfj8Xi44IILEnlpAoFAIBC0KyHLT6iuV5pRSw8zKLM/ANurdzW5r2wwYpswERAZnyEJAp6bIysri5dffpm7776bCy+8EKPRyBlnnMGf//zn8DY/+clPqK2t5eGHH6ampoYRI0bw7LPPkpWVlcCWCwQCgUDQvgTrc/zUmbTPaYZ68ZOhiZ8dNSUElSA6WRd1//TJp1Cz4iPqflhHwG5Hn57e8Y1OUpJO/GzdujXic79+/Xjqqaea3eeKK67giiuu6MhmCQQCgUCQUEJur1qjFrMTsvwUpPXGojfjDnjYV7efQlufqPubCvpgLi7Gs2sXzm/XknXmmSiKmvRFXTuCpBM/AoFAIBAIGhNye1UbAoAcFj+yJDMgo4gfD29mW/XOJsUPQI/pM0i1pZBx/PEEPG4MaVa8bh/uAN0qxYFI5SkQCAQCQRcglN25xqCVqQi5veCI62tbzc4m99fpZPJPmUDdjp2s+dVVrL30Cr659Aoq3n+PdKuhW2X3FpYfgUAgEAi6AIF6y4/bLCNLMimGI/nsBtYHPe9sJu7HYoCyhW+z7423wsuCTif7XnsDgJwZM6kLduQVJA/dR+YJBAKBQNBFUYNBlPqC3i6zTKrBGpHQMD+1Fyl6C96gjz21ZY32lyQJk9nIgfeWRj3+gSXvY7IYkSSpYy4gyRDiRyAQCASCJCdYqwU7q5KExyiF431CyJLMwAwt2/P26sauL1mWCDidBJ3O6Md3Ogk4XciyED8CgUAgEAiSgFCws5piRpWliHifECHXV7S4H0VR0Vut6KzRC3brrFb01hQUpXvM/BLiRyAQCASCJCdQH+wcsGpJfo62/MCRZIehuJ+GqKqK1+Oj16wZUY/fa9YMvG5ft5n2LsSPQCAQCARJTsjy47Nodb2iiZ9e1lyshhR8ip/dtXsbrXf7oeD8ORRc9JOwBUhntVJw0U8oOH8O7kAHXkCSIWZ7CQQCgUCQ5ISmuXvMOiAY1e0VivtZd2gD26p3UpzeL/IYQQW700/OjJkUnH8e/ho7hswMfB4/dqdf5PkRCAQCgUCQPITcXk6zFpCcGsXyA0fifpqq8xUMKtR5FbY++Qyb77ybksVLqfMq3Ur4gBA/AoFAIBAkPaHZXnUmLSYnzRg9cDmU7HCnvRS/0rQfS5VlXLv34KuqaueWdg2E+BEIBAKBIMkJFTWtMWiBzDZjWtTtellzSTVY8St+djsax/2ECMX8KE1MfT/WEeJHIBAIBIIkJ1Bv+anR+wFIjRLzA1oywyOur2ZKXdSLn6Czrj2b2WUQ4kcgEAgEgiQnFPBcq810b9LtBQ3qfDUjfmSrJp6aSnp4rCPEj0AgEAgESYyqquGp7i6zjElnxKgzNrn9oEwt0/Mux278QX/UbY64vYTlRyAQCAQCQZKheDyofk3EuM0yaU3E+4TITcnBZkwjoAQodeyJus0Rt5ew/AgEAoFAIEgyQi4v1WggoI9e2qIhkiSF63w15foSbi+BQCAQCARJS8jlFbRagOjZnY+muTpfcMTyo3q9KP7orrFjGZHhWSAQCATdCkVRCAbbXstBUSQ8Hh0+n5dgsONqYnmddUjZ2Si5GWQZZHJMWfj9vmb3GZDWjyxDOg6XHZfHiUFniFiv6nVIPbJBBW+tHX2arcPafzTx9ptOp0eW28dmI6ndpYpZKwkGFaqqGpsD9XqZzEwr1dVOAoHulREzXkSfxYfot/gQ/RYf3aHfVFXF4ajC7W6/IF9ZllGUju0vxeMh6HSi6HXUGVUsejMpBkuz+6gq1HjtKKqCzZiGQdfY1uGvqgJVRZ+egaTXdVTzoxJvv1ksqdhsWUiSFHV9VpYVna5lgSQsPwKBQCDoFoSET2pqJkajqckHaGvQ6aQOtfqAVtoiiIGASQ9mSDelYTU0PdU93DaPBXfAQ4rRGjUpos8voQYDGDJ6IptMHdH0ptvWyn5TVRWfz0tdXTUA6enZbTq/ED8CgUAgOOZRlGBY+KSmtp+LR6+XO8FSJiEhEdDJoAODwYTB0PRU9xApagpu1YefYNTtFb0eNRhEL+vQxXC89iSefjMaNYFWV1dNWlpmm1xgIuBZIBAIBMc8waBWFiL0AO1KqPVtD9YbqnRSbI9uk84MgC/oQ1EbCw2pXjyoSrAdWtk5hL6/tsZsCfEjEAgEgm5De7i6Oh0lJH40N5EsxRafo5d16GUdKuANRgmQDllOulBF9/b6/oT4EQgEAoEgCQnNRzpi+dE+x2r5kSQJk06zlHgD3sbrZU1EqR0csJ2MCPEjEAgEAkGSsWrVZ9xxx63AEfGjyBISIMcofgDM9eLHE2wsfgjNiupCbq/2QgQ8CwQCgUCQZLz22stAvfWn3jKjyJrwaY3rx6TXxE8o7qehcDoS8yMsPwKBQCAQCJKF4BGrjCLF7vIKYZD1Tcb9hNxeXSnmp70Qlh+BQCAQCJKIa6+9mnXrvgNg8pTxZKVncPzwEVw5/wZk+Uiw80UXzWH06BO56ab5XHDBLKZNOwePx83Spe8hyzITJkziuuuux2wwUae48AS8bNu4mf/85wk2b96I0Whk/PEn8JvLriQ3Ly9Rl5sQhOVHIBAIBIIk4vrr/8ygQYMZNGgw/3rkSU6bMIkv136D2+UOW37Wr1/Hvn17mT59Vni/RYve5Mcff+CWW27lN7+5lq+++oI//en3GGUth8/369Zy3XXXYDKZ+fvf7+F318zjh80buX7BzXi9noRca6IQlh+BQCAQCJKIoqJiUlK0DM7DBw8hxedl4Qfv882qL5k581wAli17nz59+nLccceH95NlmYce+hepqVrh04yMTG6++QbWf/c9BcOLeOnpZ+nTt5D77nsInU6H4vcxqGcOv7rpD7z33rvMnfuTzr/YBCEsPwKBQCAQJClqMEhBr94MHzKUVZ98ik6S8Xo9/O9/H0VYfQBOPvmUsPAJfdbpdPz4ww8EfX62b93GuJPGo6oqgUCAoKLSKyeXvr3zWbNmdWdfWkIRlh+BQCAQCJKU0DT3aWecycP/fIyqQ5Xs2LwVl8vF2WfPiNi2Z8+ciM+yLJORkYHDYSfg9qMqCq+/+jKvv/pyo/NYUhvX/jqWEeJHIBAIBIJkpT4Hz8RJE3ni6f+w8rNP2bxhI2PHjm8kduz2mojPwWCQmpoaMjOzyLRlIkkSM+acx3nT54S38ZYfAEUlrU/fDr+UZEK4vQQCgUAgSDJ0uvrsy/WWH4PFzPhTTuazT1awZs3XTJ8+s9E+X331BX6/P/x51arPCAaDnHjiWDLTMunXv5h9e/cwaPAQhgwZxpAhwyjqW8jzC1/n++/Wds6FJQlC/AgEAoFAkGSkpqayd+8evvvhe2qddQQklSlnncHWrVswGIxMnjyl0T4VFQe56aY/8tVXq1i8eCH33HMHJ500kRNOGINe1vPzy3/J+m+/59YFt/DVV6tYtepz/nz37Xy/aQMDBwzs/ItMIEklfkpKShg9ejSLFi2Kun7+/PmcfvrpEcsUReHRRx9l8uTJjBo1iquuuoq9e/d2RnMFAoFAIOgQ5s79KXq9nr/cdRvf/PA9igQDhwzGZrNxxhlnYTQaG+0zdeo08vML+NvfbuaZZ/7N9Okzueuu+8Lrx42bwE133EpFRTnz59/EHXf8DZ1Ox31//ivDBw/tzMtLOEkT8+P3+7nhhhtwuVxR13/88ce8+eab5OfnRyz/17/+xSuvvMI999xDXl4e999/P1deeSVLliyJenMIBAKBQJDsnHDCGN56awnePbtBVTksw66t23A4HMyePSfqPgaDgeuvv4nrr78p6nqz3syIUcdzwolj6GXNBcB3qALF6ex2JS7iFj9VVVU8/fTTfPnllxw6dIj//ve/fPzxxwwZMoQzzjij1cd77LHHIqboNaSiooK//vWvjBs3jrKysvByn8/HM888ww033MCUKVMAeOihh5g8eTLLly9n5szGPlGBQCAQCLoEigKqyrpNG/myZBMrV3zKuHHjGThwUFyHC1V49wf9BJUgOlnXoL5X9ypuGpfba+/evcyePZs33niD3NxcKisrCQaDlJSUMG/ePD799NNWHW/NmjW8/vrr3HPPPY3WqarKn//8Z84991zGjRsXsW7Lli04nU4mTJgQXmaz2Rg2bBhr1qyJ59IEAoFAIEgKQtYYR10t77/9LhlZmdx00/y4j6eXdRhkfWSdr25a3ysuy8+9995LdnY2L774IikpKYwYMQKABx98EK/Xy5NPPhm2xLSEw+HgxhtvZP78+fTq1avR+ueee45Dhw7x5JNP8tRTT0WsKy8vB2i0X05OTnhdW9DrG2tDnU6O+FfQMqLP4kP0W3yIfouPY73fFCX2SuixEiquLkmgqu1++PA098kTJzH47Mmk6M30TOkRddO33loS0yHNehN+XwBv0EuKwYIU+r470e3VHv2m00lRn9GxEpf4+eqrr7jrrruw2WwEg5Gmsp/+9Kf8/ve/j/lYCxYsYPTo0cyaNavRui1btvD444/z8ssvR43fcbvdAI3WmUwm7HZ7zG2IhixLZGZam1xvs1nadPzuiOiz+BD9Fh+i3+LjWO03j0fH4cNymx+a0egowRjw1CuDeteUXqdvc9tTjBZqfU68QS96vYyq1xMAUJV275eWiKffFEVClmXS01Mwm81xnzvumB+9PvquPp8PSYpNYS9evJi1a9eyZEljxer1ernhhhu45pprGDJkSNT9Qxfu8/kiOsHr9WKxtO0HrCgqDkfj4GudTsZms+BwuAl2MzNhvIg+iw/Rb/Eh+i0+jvV+8/m8KIpCMKgSCLTP9UmS1m/BoNIhlp+gPwBAyGglIbW57QbJAEBADeIPBFDRDq4Gg+3WLy3Rln4LBlUURcFud+F2N45TstksMYmquMTPmDFjeOqpp5gwYQImkxZAJUkSiqLw6quvcsIJJ8R0nIULF1JZWdnIRXbrrbfy9ttvs337dh5//HH++c9/AtqMsEAgwOjRo/nPf/4TdndVVFTQt++R7JQVFRUMHjw4nkuLoLkbIRhUOu1GOVYQfRYfot/iQ/RbfByr/RYMtr86CT24O8TlxZEEh4osASqy1HbLjE7S0SstB7PehKIqSIb6ZIqd6PZqj35rq4iNS/xcf/31/OxnP2PatGmcdNJJSJLE008/zc6dO9m9ezevvPJKTMd54IEH8Hg8EcumTZvGvHnzmD17dqN1L774IsuXL+fFF18kNzcXWZZJTU1l9erVYfHjcDjYtGkTF198cTyXJhAIBAJBUhASP8F6y49O0rX5mLJOwuPxUFF3mKCqYFQgEzo15icZiEv8DBo0iIULF/LYY4+xevVqdDodX375JWPHjuXee++N2eqSm5sbdXl2dnbUdenp6ej1egoLC8PLLr74Yh544AGysrLIz8/n/vvvJy8vj2nTpsVzaQKBQCAQJAVhy4+kmUh0bbT8SDLUeBxUux3hZQHU8Lk6LHA7CYk75qdfv348+OCD7dmWuJg3bx6BQID58+fj8XgYO3YsTz/9NAaDIdFNEwgEAoEgfupnewVkFZCQ22j5kSUJh6c2YpnaQE9JqOEYoGMdSVXj03k+n49du3ZRW1sbdf3YsWPb1LBEEwwqVFU5Gy3X62UyM61UVzuPSb94RyD6LD5Ev8WH6Lf4ONb7ze/3UVl5gOzsXhgM7Zf9X6+XO6y/vGX7UP1+qtN0+AwyBam90MnxCyBJVimtKWu0PKfaj6SCuU8B6DrHcBBvv7X0PWZlWTsu4Pmrr77i+uuvp7q6mobaSZIkVFVFkiQ2b94cz6EFAoFAIBAQGfAsAbIk87vf/Rqn08kzz7wUdZ97772Ddeu+Y8SIkSxb9l7EOp1OR5rNxvBRI7n46l9hS08H4L6n/slHn38asa3JZCI/v4ALLrioyXIaXZm4xM9dd91FVlYWCxYsICMjo52bJBAIBAJB90ZV1XAQsiJrwkeSJGbOPJfbb/8bu3eXUljYL2Ifr9fL//73MZdccjmlpSWMGDGSO+88UtjU5/fyzXer+ecjD1NXW8uNf/+bdi5g2MBB3HnnfcgmLW2Mx+Nh6dIl3HffnaSlpXHaaa0vW5XMxCV+9uzZw7/+9S8mTZrU3u0RCAQCgUDQIIGwIoGxPth5ypTTeeih+1i+fBlXXXVNxC4rV36K2+3m7LNn8OSTj6PX68nOjswIPWfWXA7s389Lzz2Hy+kkLTUNSZLQ6/RkpWeisx5J7nvVVdewYsVHLF/+gRA/AIMHD+bAgQPt3RaBQCAQCDodVVXx+eOL2wkqbcs3YzTIURMDh1xeqiwDEnJ9rI/JZOaMM87io48+aCR+li17n4kTT24keBqiBFVsKZrgKcwqIC0lNXxsNdg4aaBer8NoPPYmEMUlfm6++WZuuOEGdDodI0eOjJpNuXfv3m1unEAgEAgEHYmqqtz90nfsKGtbSaR4GVCQzl9+cUIjARSush6qudZgmvuMGbNZvHghGzasZ8SIkQBUVh5m7drV3HXXA02eS1VVNmxYz+uvv8qEk0/GHqjD72ogeBrk+nG5nCxc+CalpSWNRNaxQNxT3X0+HzfffHOT60XAs0AgEAi6BMk4u7u+xIhSL4oaTnMfOnQ4/fsPYPnyZWHx8+GHy8jMzGL8+Inh7davX8eZZ04Of/b5fGRkZDJ16pn89JcX4wn6McoGkCQ2bN3M2RfMDE9c8ng8ZGZmcc01v+PUU0/vjCvuVOISPwsWLECv1/PHP/6RHj2aNq8JBAKBQJDMSJLEX35xQtxur7ZOdW/Z7aV9PjrB4YwZs3nhhWeZN+969Ho9H374PuecMxOd7ohIGjx4KLfeegcApaUlPPTQfQwcOIgrr7yGoF7B46lBURWQJAYV92f+DX9Bn5mFJEmkpKSQmZkV93UlO3GJn127dvHoo482qsklEAgEAkFXQ5IkTMb48ufo9TI6uf1NR0fX9Tq6tMW0adN54onHWLPma7Kze7Br107uvPP+iG1MJhMFBX0AKCjoQ35+AVdffSkLFtzM3+64E4BgvfgxGoz0zsnD2ETlhWONuHJlFxYW4nI1rnguEBxrSJKEThf9zUwgEAg6DCWyrtfRRU0zMjKYNOkUVqz4iI8/Xs6oUSeEhU5TFBUVc8018/jyy1UsW7JEO42qhMe3cJxRNyAu8XPdddfx0EMP8cUXX+B0Ns6CLBB0dXQ6mVSzTFa6iVTZr/1rkmPKHCoQCARt5UhR06bres2ceS5ffLGSTz9dwcyZ58Z03DlzLuD440fz338/QdXhSs3tFaIbFTeNy+314IMPcvjwYa688sqo6yVJYtOmTW1qmECQKHQ6mXSrgX0LF3HgvaUEnU50Viu9Zs2g4Pw52J1+gsHuM0gIBILOJ1L8HJnq3pBx48ZjsVhwOOxMmRJbULIkSdx003wuu+znPPuvp7jhbzeDHLL8dJ9xLS7xM2PGjPZuh0CQNFgMsG/hIva9/mZ4WdDpZN9rbwCQM2Mmdd3HOiwQCBJB/QtWyO0VzfIjyzKLFr0fdfdbblnQ5KH79i1kxYpV7KktQwX+/Oe/EigrA0UJl6g61olL/Fx77bXt3Q6BICmQJAmT2ciB95ZGXX9gyfv0ueB8nD4vcdYEFggEgmZRVTUcf6OVtpAaxfy0FUmSkCUJRVVRQlpHVbU/IX6OsGbNGoYNG4bVamXNmjUtbt/Vq7oLuieyLBFwOgk2EcsWdDoJOF3Isp5gUIgfgUDQASiKJkLQSltEs/q0BzpJRlGDKNQLnnrRJcnHfmxjzOLnkksu4Y033mDkyJFccskl4URIDRFV3QVdHUVR0adZ0VmtUQWQzmpFb01BsXsT0DqBQNAdCMfeSBKqJDWa5t5eaIkTgyiqgizLWj2xoNKG9Mddh5gv8YUXXqB///7h/wsExyKqquL1+Og1a0Y4xqchvWbNwOv2CZeXQCDoOEIJDutnl7a3yytE6LiKGkQn61CDwW4T9Byz+Bk3blz4/5IkhV1gR+NwOFi5cmX7tE4gSABuPxScPwcUhQPvL4s620sgEAg6iiPZnbXYm450e4GW6NAoy6jQbaa7x2Xc+uUvf8nrr7/OyJEjG63btGkTf/nLX8SMMEGXJRhUqK6qI3VAf8Y+82/8dgeGdBs+r19McxcIBB1OWPxIIfHTUW6vkOVHCRdQ7S6JDmMWPzfddBMHDhwANNfAggULSE1NbbRdaWmpqPcl6PLUbd1K2UMPYO5XiN5qxbN3H72uuRbLwEGJbppAIDjWUSJLW8gdFIAcElVBVTkS5NxNLD8x9+hZZ52lTb9rEOsQ+hz6k2WZUaNGcffdd3dIYwWCzsK9dQsAxl4FYLQQcDhw79yR4FYJBILuwJEEh9rnjrf8BKE+iaLaTSzbMVt+Tj/9dE4/Xcsgeckll7BgwYJwAHRz7N+/n5ycHPT6bhA+LjhmcG3bCoBl8GCCdXXUff8tnp07E9wqgUDQHQgJkKDcdGmL9qCh20uSDdrCbuL2iqtHX3zxxZiETzAYZOrUqWzdujWe0wgECUHxevGU7ALAMmgIlv4DAHDv2iFmeXUBQvnZukGeNsGxylF1veQOsvw0DHg+EvMjLD/tgnhYCLoanl07IRhEn5mJoWdP9BkZoNMRtNsJHD6MoWfPRDdREAWdTsZiAJPZiM9ux2ZNwev24Q4ggtQFXYpQ0HHIBtPQ8vO73/0ap9PJM8+8FHXfe++9g3XrvmPEiJEsW/ZexDqdTkdGRgZjxozj2mv/SKpNi9v95wMP8fnHn0RsazKZyM8v4IILLmL27DlNtnXp0iXcdddt4c+SJGGxpNC//wB++tOfM2XK1JivuzMRviiB4CjCLq9Bg5EkCcloxNSnL97SEty7dgjxk4SIYrSCY4lQzI8ig0Rknp+ZM8/l9tv/xu7dpRQW9ovYz+v18r//fcwll1xOaWkJI0aM5M4774tYv2HDev7xj3ux2+3ce9/D2vlQGT5sOLf+9jokgxFjXh4ej4elS5dw3313kpaWxmmnndFsm9955wOtzYpCTU0NH320jL/+9c/86U83NyueEsWxn8NaIGgloWBny6Ah4WUh15dHBD0nJQ2L0YYyc4eK0e5b9DYW8Zon6CKoqhqecaXV9ZIjCo1OmXI6qampLF++rNG+K1d+itvt5uyztVQzer2e7Owe4b/evfOZNu0cfvrTX/D111/icjoJHVmvN5CVkUmmzUZ2dg/y8wu46qprKCjoy/LlH7TY7tA5evbMYeDAQfz2t9cxd+5PePzxh3E47G3tlnZHiB+BoAGK36e5vYCUwYPDy8NxPyLoOemIpRityWLsFpWqBfGhqiqq35uYv6NCQ0JWH5Ci1vUymcycccZZfPRRY0GybNn7TJx4MtnZzaebMRq134Nerz9iVQr9PI6K+dHrdRiNhpj7siEXXvgzXC4nX365Kq79OxLxPiQQNMBTUoIaCKCz2TDk5oWXm+vFj3ffXhSvF9lkSlQTBUchitEK2oKqqrjevRPlYGKsurrcgVhm33xEnIdLW0iAhCw3DnaeMWM2ixcvZMOG9YwYoSUbrqw8zNq1q7nrrgeaPJeqqmzYsJ433niVU089DYvFglynWWXUIxuhKgpuj5uFC9+ktLSEq666Jq5ry88vwGw2s2PH9rj270iE+BEIGtDQ5dXQUqDPykKXkUGwpgbP7lJSBg1u6hCCTkYUoxW0FYnksQqGMyzXJx2MNs196NDh9O8/gOXLl4XFz4cfLiMzM4vx4yeGt1u/fh1nnjk5/Nnn85GRkcnUqWdy1VW/jTj+hh/XM/OKS6C+wrvH4yEzM4trrvkdp556etzXk5qahtNZF/f+HYUQPwJBA9z1wc4NXV5QP4Oh/wDqvl2LZ+cOIX6SCFGMVtAWJEnCMvtmCPji2l+vlwkE2hBMrz/KJRsMxftoy5qa5j5jxmxeeOFZ5s27Hr1ez4cfvs8558xEpzuy/eDBQ7n11jsAKC0t4aGH7mPgwEFceeU1WCyWiOMPHDSYm399LQSDmPJ6YU1PJzMzK3ys8vJyLrnkwog2fPRRy3U8nU4nqalpLW7X2QjxIxDUowYC4SzODYOdQ5iL+1P37VqR6TkJEcVoBW1BkiQwxOfKlvQyktR+Mwkj63qpTSY4nDZtOk888Rhr1nxNdnYPdu3ayZ133h+xjclkoqCgDwAFBX3Izy/g6qsvZcGCm7n33oeQJClcOsNgMlLQOx/V78eQl4fObIk4Vo8ePXj22VdadS179pTidrsYODD5XhY7VPzIssy1115LTk5OR55GIGgXPKUlqD4futQ0jL17N1rfcMaXqqoigDaJCAYV7E4/tuHDKJg7p74YbTo+X0BMcxd0KRpOc4emsztnZGQwadIprFjxEVlZ2YwadUJY6DRFUVEx11wzj3/8417eeWch5513wZHjq2rY1UaU34ter2/x+EezaNGbWK1WJk06uVX7dQYxi5+//OUvMR9UkiTuuusuJEni2muvjathAkFn4w7n9xkUVdiYCguR9HqCtbX4Dx3CKER9UhEIBNl5933IRiPGzAx81TUU3nE3uhRropt2zKNZECQURRXuxbZyVF2v5rI7z5x5LrfdNp+0tDSuuOLXMR1+zpwLWLFiOU888RiTJp2CKV2z8KiAJOtQiS/Lc2XlYe04qkp1dRUrVnzEokVvcuONt2C1Ni6CnmhiFj+rV6+O+aDijVjQFXFFye/TENlgxNS3EM+unXh27hDiJ8lQ6upQPB4UjwdJJxNwOPDu2UPKkKGJbtoxS8Os2gGnE32aVWTVbiPh7M5Sy3W9xo0bj8ViweGwM2VKbEHJkiRx003zueyyn/Pgg/fw19vvCJ25TZXdzz337PDxrVYrw4eP5IEHHmXcuPGtPlZnELP4+eSTT1reSCDooqjBIO4dWixPw2Dno99ozf0H4Nm1E/euHdgmTGzqcIIE4Dt0CAB9RiZpgwdR9fVqIX46EJFVu2MIub0CkkpTU91DyLLMokXvR113yy0Lmtyvb99CPvnkCwDcAQ+/+eN1GHUG8Ibqe8Ve3HT69FlMnz4r5u2ThTYlObTb7axYsYJXX32Vqqoqdu3aJUyegi6JZ/duVK8HOcWKMb8AnU7GbNWRnmlGtgRJzzRjtuqwDhyobS+SHSYd/sMVABhyepJaXASAZ09pAlt0bCOyancQodle9Q6UjqroHiKU5DCoBJFCQqsbiNa4b88nnniCp556Co/HgyRJjBw5kocffpjq6mqeeeYZbDZbe7ZTIOhQ3NtCLq9B6A16rDYD72z5kGXbPsXpd2E1pHDOoCmcM2oMZdQnO/R4kM3mxDZcEMZfoYkfY8+eWOvFj3fPnkQ26ZgllqzafS44H6evcQZjQdOoqhq2umilLaSIul4dQUhcKaoSDnjuDpXd4+rVl156iccee4zLL7+cN954I3xzX3zxxezdu5dHHnkkrsaUlJQwevRoFi1aFF72ySefMHfuXEaPHs3pp5/Ovffei8fjCa/3er3cdtttTJgwgdGjR3P99ddTVVUV1/kF3Zdwfp9BgzGYJd7Z8iFvbVyK0+8CwOl38dbGpSw7tBZDVhYoCp7SkkQ2WXAU/sOa28uYk4u1uBgA34H9KF6R3LC9iT2rtoj/bBWKos264khdr44mdA4VUEPfVyvcXl2VuHr2xRdf5Oqrr+a6665j+PDh4eWnnnoqv//97+OKD/L7/dxwww24XK7wsrVr13Lttddy5pln8vbbb3PrrbeydOlSbrvttvA2CxYsYNWqVTz22GM8//zz7Nq1i3nz5sVzWYJuiqoouLdvAyBl8BDMJiPLtn0addtl2z4lbYgWEyTy/SQX/vqYH0PPnhizMtHZbKCqeMv2Jbhlxx6KoqK3alm1oxHOqq0Iq09rCFtcJAkVqcNdXqCJH7l+kpIa+ldYfqKzf/9+xo0bF3VdcXExhw8fbvUxH3vsMVJTI6fDvfbaa5x00kn85je/oV+/fpx66qn84Q9/YMmSJfh8Pg4ePMjixYuZP38+Y8aMYeTIkfzjH/9gzZo1fP/99/FcmqAb4t27B8XtRrZYsPTrh9PnClt8jsbpd2Ec0A8QFd6TjZD4MfbMQZIkzIX9APDu2Z3AVh2bNMyqHQ2RVTs+wgkOddqjublp7u1J2PoTUgRC/ESnV69eTYqLDRs20KtXr1Ydb82aNbz++uvcc889Ect/9atfcdNNN0Usk2UZv99PXV0d3377LQDjxx+ZSldUVERubi5r1qxpVRsEHUco80GyZkBwb63P7zNgICoSVmMKVkNK1G2thhSyhmnWTo8I8E8aFL+fQLXm7jb27AmAubAQEOKnowhl1S746YVhC5DOaqXgop9QcP4c3IEEN7ArEhI/9e6nzrD8wBHxEwqyVkXAc3QuuOACHnvsMcxmM1OmTAHA5XLx4Ycf8tRTT3H55ZfHfCyHw8GNN97I/PnzG4mmYcOGRXz2+/0899xzjBgxgqysLA4ePEhmZiamoyps5+TkUF5eHs+lRaDXN77xdPWKPPSvoGlkWcKkA6PJgM9ux2ZNwef14w2SVOZwz3ZN/FiHDkWnk/D6fJwzaApvbWwczHnOoCnoCvKR9AaCdbUolYcw5eU12q49EPda7HgPV4GqIhmNGLMyAbD260clmmUv2m9ZEEk891udJ0D68SMpOP+8+qzaNnxuL3WeAJIUfQxNFIoS+fYlSSABkixplg5ZRlVULfYlxuGp4Ytdu7wHKUeJn2amubcnugbiRwegKtSnPeyQ87VHv+l0Upvur7jEz1VXXcW+fft44IEHeOCBBwD45S9/CcCsWbP49a9jyzQJWszO6NGjmTWr+TwBgUCAG2+8ke3bt/Pyyy8D4Ha7MRqNjbY1mUx42xjkKMsSmZlNZ4a12SxNrhNoKD4fe9+KzAHSe9YMCubOQY7yvSUCVVHYtkOL98kbM4q0+u/8vKFno6oqH2z/LGK213lDz8aoM5A6oJjaLVuRD+wlc2j/Dm2juNdaprqkFgBLrzzS0zWrXY8RQ9gDePfuJT3NhKwXc69jobX325rfP4QSCGDqkY33cCUDf/dbssaN7aDWxY/Ho+PwYTn80FRVFV91Nf4ae1j8GDMyMGRmtDpRb3u9oCjhYGetrpdBp+8UARkSWWqDU+kkkDr4xSueflMUrR5ZenoK5jbMto1rNJAkib///e9cfvnlrF69mpqaGtLS0hg7diyDBg2K+TiLFy9m7dq1LFmypNnt6urq+P3vf88333zD448/zsiRIwEwm834fI0r8Xq93nDF2nhRFBWHo3Hch04nY7NZcDjcnZ7AS5K0vldVtX3eMjoQi0Hi4Lvvsu/1N8PLgk4ne197AxXInTULtz/xF+HZu4dAbR2SyYQ/K5fqam32yk57CcWZfXly9l3YvXXYTKm4vV7cdX6cig9Dv2LYspXD6zdiGN0xA30i77WuRtUubUq7nJWNw+HGZrPgs6QhWywobjcHN23H3KdvgluZ3MRzvwVqavBVVYEkYRk0mMCuEg79uBlp4LCWd+5kfD4viqIQDKooQQW/vQZ/VfWRDRQFX1UVKmBITycW47Qkaf0WDCrtMiYH/VoB3nDvq1LbKsbHiFwfARNQguhlGRSFgM+PZOg4y0+8/RYMqiiKgt3uwu1uPCvNZrPEJKriEj/PP/88s2bNoqioiKKiongOAcDChQuprKwMu85ChGZ1/fe//6WiooKrrrqKsrIynn76acaOPfKgycvLo6amBp/PF2EBqqioIDc3N+52hWjupgsGlU65KSFKCnlrcqeQlyQJY2rLOUDqPInPAVK7aTOgxfsEkaH+O127fz2f7F3J1L6TqQ3UsrlyBxcOmM2JuaMAMBVpU6md27d3+H3QmfdaV8V7UMvxo8/uGf5NKCqY+vTFvW0rzl2l6HsVJLKJXYbW3G/OklIAjHm9MA8aTO3aNbh27UrK+zUYPDLWSLKkWXyi4K+pwZiZAcGWx6bQ8NVew1go1iYoaweMNtX9d7/7NU6nk2eeeSnqMe699w7WrfuOESNGsmzZexHrdDodGRkZjBkzjmuv/SOZmZqL+OH77mfF8g8jtjWZTOTnF3DBBRcxe/acJtv83XdrmTfvNxHLJEnCYkmhuLg/V175G8aMiZwg1R79FgyqbbrP4hI/999/P/fffz8TJ07kvPPOY+rUqY3ibmLhgQceiMjZAzBt2jTmzZvH7NmzsdvtXHrppdTV1fHyyy8zuEHZAYATTzwRRVH49ttvmTBhAqDlCjp48GCESOrKdMUU8rHnANFHDEiJ4Egx08h7a0vVdgAK0/qyo6aEWm8dJY49YfETqvDuK9uH4nEjm4VrKpH4DtVnd64Pdg5h6luIe9tWLeg5CStLd3U8u0sBrZ/N/eoTS5aWoqpqctd4VJSmZzSF1yWg/eHSFtrHaAHPM2eey+23/43du0sprJ/RGMLr9fK//33MJZdcTmlpCSNGjOTOO++LWL9hw3r+8Y97sdvtPPDAo4BmiRk4dDB/ufVW0hx+VJ+XYJqNDz75iPvuu5O0tDROO+2MZpv+n/88T06OZnRQVZUDB/bz1FP/5MYb/8Arr7xFXl7rJkJ1NHE59FauXMnNN9+My+Xi+uuvZ+LEifzlL39pVfFTgNzcXAoLCyP+ALKzs8nNzeXuu+9m79693H///WRlZXHo0KHwXzAYJDc3lxkzZjB//nxWr17N+vXr+eMf/8i4ceMYNWpUPJeWdHTFFPJdJQeIqqoNkhseKWZq9zrY7yxHQmJw1gCK0jV3San9SLZgfUYm+uxsUFU8JSLZYaI5kuMnstisua+Y8dWRhPrVXNgPU58+oNMRrKslUNn6dCediiyHsxm3al0H07ioaeOA5ylTTic1NZXly5c1Wrdy5ae43W7OPltLQaDX68nO7hH+6907n2nTzuGnP/0FX3/9JXV1dQBISOj1emyZGWRnZ5OVkUmv3FyuuuoaCgr6snz5By22PSMjM3yeHj16ctxxxzN//t/x+bysXPlZnD3SccT1DWdmZvLzn/+cl156iU8++YTf/va3bNu2jcsuu4wpU6bw4IMPtrlhwWCQpUuX4vf7ufTSSzn55JMj/g4cOADA7bffzoQJE7j22mu54oorKC4u5tFHH23z+ZOBWFLImyzGpHvD6io5QHwH9hOsrUUyGjE3cN+GrD590nqTarBSZNMeoHtry/ArR+bvhqw/ItlhYlFVtUGOn6MsP6Hp7nv3dInEbZIkodPJSfebboqw5aewENlgxJSvuRaTPfu5qqgYMtKPfFZVvIofr+JHSUvB4/fiDfpi+wu0Ytsofw3HwVCeH6V+Jlo0t5fJZOaMM87io48aC5Jly95n4sSTyc7u0ez1G43G+ntNE1dSvZWrYYmLUH0vvV6H0WiIvXMj2mqsP0byvaW3uUW9evXiiiuu4Mwzz+SFF17g1Vdf5b///S/XX399XMfbWp9zBWD9+vUtbp+SksIdd9zBHXfcEdf5kpmu5D46mlAOEFQ10l03c3rYXZdoQvl9zMX9kRr8ODfXi58hWVrwfg9LFqkGK3V+J/tqyyhKL6zfbwC136wWyQ4TTLCuFtWruc/1PSIHfWNeLySDAcXjwX+oAmNux6QlaCuN4vrSkjuuDyBYV0egshLQYqsAzEVFePfsxlNSQtqY6IlwkwFFVTGmp4MKvpoaHi97m1JvfXqU0s5tS3F6P/54wjX1DauPV6svbdGUCJ4xYzaLFy9kw4b1jBihTQCqrDzM2rWrueuuB5o8l6qqbNiwnjfeeJVTTz0tPDEodB5FVZBkTeg46+p49923KS0t4aqrrmn1dVVWHubhhx/AarUyefKprd6/o2mT+CkvL2fp0qW89957bN68mezsbC6++GLOPffc9mpft0ZRVPRpmvsomgAKu4/syVe7KBhUsDv9ZJ40LiIHiKviUNLEKYWKmaYMPuLyUlWVrdWa+BmapVVwlySJovS+/Hh4MyX23WHxY+mvTXF379qZ/DEOxzChgqb6zExkQ2QKBUmnw5hfgLe0BO+ePUkpfrpiXB+Ap97lZcjJRZeipRcw9yvC/tmnSW/5CdTW4at1YMzOxtqvH7rDJkjwMBqy+oCEIoGhmQSHQ4cOp3//ASxfviwsfj78cBmZmVmMHz8xvN369es488zJ4c8+n4+MjEymTj2Tq676bXi5hMSWjZu5dM5PNBuQquLxesnMzOKaa37Hqaee3mL7L7nkJ+ExMHS/jho1mscf/w89evRsbteEEJf4efnll1m6dCnff/89RqORqVOn8vvf/56TTz4ZOUG+0mORsPto5vSIKeMhksV91BTBoMKe517CW1qCJb837rL9WEedQO4vL0t001BVFVeUYOf9znIcvlqMsoGi9H7h5f1shZr4cRyJ+zH16atZFZxO/AfLMSZZQF93IVTQ9Oh4nxDmwkK8pSV4dpeSNjb5rBEN4/pChOL6AHJmzKQuCetMendr4sdUH1cFHAl63l2KqihISfg8UFUVxWFH9fsJeLxI/gD/l3cu/gIw9Ih+DzWHXicRaIPl3SgbtBQm4dIWEiBFjfdpyIwZs3nhhWeZN+969Ho9H374PuecMzPsygIYPHgot96qeUVKS0t46KH7GDhwEFdeeU2jdDDFA/rz2xv/SK6aglJbizUzi9yBR1LXlJeXc8klF0bs89FHK8P/v//+R+jZMwen08lLLz3Hxo0/ctllVzJwYOzpbzqTuMTPnXfeybhx47jzzjuZNm0a1iYCWwVtx+2H3rNnau6j95dFfStMZrx79xJwOEg99RRqN2/BU7Ir0U0CwH/wIEG7HUmvx1xfARxgc5WW8HBARjEG+cjPo7g+6LmkQdCzpNdj7leEe/s23Dt2CPGTIMLBzk28XYYezt69e6KuTySxxPX1ueB8nL7Ep4U4Gu+eUuBIGREAY+98JKMRxePBV16OqXfvBLWuaRSPG/x+kGV0aWkoPh+q349B1WPStT75ql4vo6PtlrlQsHMo5kbXgnCcNm06TzzxGGvWfE12dg927drJnXfeH7GNyWSioKAPAAUFfcjPL+Dqqy9lwYKbuffeh8KWGkmSMJpM5PXuRZ6UhlpZ1WgGa48ePXj22VeabE9eXi969dK+7wUL7uT663/Hn/50HU8//VK4DclEXLL8f//7H8899xxz5swRwqeD8dU52fDXBaT278/Y5/7Lif9+grHP/Juc6dOT1hweIlhbG663lDdNmybpLduHEiUxZWfjqnd5mYv7R7hKtoTjfQZGbN83rQ8SEtXeGmq8R/KDmOuDnj27jq24n64UeNuwmns0Gs74SjYBEUtcn99ux71xPUG3u9ljdfZ3FnJ7NbT8SDpdOP7Hm4SuL1XVYpUAdGlpSLKMbNBiXNRAIKFB8eFg5/rSFi0VNc3IyGDSpFNYseIjPv54OaNGndCiyCgqKuaaa+bx5ZereOedhRHrQneNGqrvdVRf6PV6Cgr6RPw1hU6n45ZbFiBJMnfccStKEk42iEv85ObmcvDgQZYuXcrixYvDf4sWLeLll1/mD3/4Q3u3s9tS+83XuHaVsOvZF6iq8bD1kcdYe9U1VPywKamFD2jZkwEMOTlY+hSgT08HRUmKacfhYqYNMpL7g3521GgD9tHix6w30TtVixdpOOU9HPezc2eHtrez0OlkUs0yWekmUmW/9q9JTur6Yv4mcvyEMBYUgCzXi/HqqNskipjSQqSmsv+//2HXH35H2aMPYV/1efgBDon5zoJuN/6DBwFNXDYUXqGZk8kY96MG/Kg+H0gS+jSbtrDB1HY1kMBqrPXjuSrFXtR05sxz+eKLlXz66Qpmzowt1nbOnAs4/vjRPPHEYxyq/+0A4YJb4RJoStt8rT175nDttdexYcN6Fi16o03H6gjicnt98MEH3HDDDQQCgfBbRsOAz+IGbgRB/Kiqiv2zTwFIP2UKSBJyeiaBjZtwbviRlKHJl0K+ISE3Q2hwNBcXU/f993hKdmEZMLCFvTuOhvl9LA3y++yy78av+LEZ0+htbRwYW2TrS1ndAUocexiVcxygzfgC8O0vI+hyhQM/uyJdNfD26Bw/DYsmAsgGI8ZevfGV7cO7ZzeGrKxENDMqLcb1zZyOc99+pJQUVIcD5/ofcK7/gYPyc6QMHkLmqVMoOO1kyha93anfWei3rc/OxpqXgdlkxOlzkWZMwTW4PzUff5SU4kdxu8FoRZeaGp7hKUkSksGA6vWi+v2QoLqDRyw/2udYxM+4ceOxWCw4HHamTGk5KBm0673ppvlcdtnPefDBe7jnnn9oy+vXK5JmFWkPK9jMmefx0Ucf8tRT/+Lkk6eQ10FFoOMhLvHz5JNPMnz4cG699VZefvllgsEgV111FZ999hn/+Mc/uPnmm9u7nd0S7+5SvHt2I+n12CZOAiBl+HE4vvwC54Yf6XnhTxPcwuYJJ0CrN4tbivpr4ifBg6L/8CHNHafThXP1AGypPuLyiuY66JdeyKr9qymxH7Fc6dPTMfToif/wITwlu7AOH9HxF9BBdMXAW8XvI1CjWXPMeXmYrTrMJiN2Ty3WNAserw+/R8XctzAsflJHjU5wqyNx+6H3rBnNxvX1u/1ufPv3U/fdWuq+W4t3715cmzfRd84syhYuYt8bb4WP1xnfmbc+v09q/yKW7VrBsm2fhgsAz8oaTS71uZUCgYg0EonEd+BAvbgBnS09Yp1sMBAMiZ8EERI/wZBob8HtBSDLMosWvR913S23LGhyv759C/nkky8itq10V1HndxGU6oWBosQ0i/WEE8awatXaJtc/8sgTze6fKOK6K0tKSnjwwQcZNmwYJ510Es888wz9+/enf//+HD58mCeffJJJkya1d1u7HfbPPwUg9cQx6FJTAbAOGw6ShK9sH4GaavQZmQlsYfMcsfxoMQCW4npzeIIzIofz+/QrQm5QliUU7DwkM7pVqtimXcee2n0ElWC4ErK5f39N/Oza2WXFT1cNvA1UVoKqIplM2PKzeHfr8ogH8TmDpnDukLOw9CvE8dUX4TiVZMJzuJLSRx6g8JKLGff80wScLvTWFLxuX9hyI0kSpvx8TPn5ZM86F9/Bg7g3biBj1PFsf+TxqMftyO8s1I970oK8tfHIPeP0u3itfBW/MxuQPX68+8vCLz+Jxr7qczh+OLLZEo7zCSHVx/0p/gTGIzbK7ty5ruaQ2FKkBveKooCuZRHWFYmrd7Vy8ppyLiwsZNeuXeGAplNOOYUdO46t4M9EoHjcOFZ/DUD6qaeFl+vS0sLTSZ0bNiSkbbGgeL346rNwh2aDWOrb7a84GBGz0NmE8vs0nOJe53Oyr3Y/0DjeJ0TPlB6k6C34lQD76vaHl5uPgUzPsizhr4sloWZyBUCHXF6mnBze3bqctzYuxel3AdqD+K2NS3lny4dYB9ZPwd6TfDO+6r5bi3tfGaVvLKTK7qVO0Wv/epUmXVbG3FyyzjyToNudkO8sNM39S8oar5QkDmRqD8xkCXr2Hz6E88cfAG0MPRopFPScFJaf+qKmcueKjpDYCjbI8twVsqLHS1zip7i4mO+++y78f5/Px5Yt2gPF4XDgS4LZPF0dx+qvUb1eDHl5WI7Kk5AyQos3cW74MRFNiwlvWRmoKrq0NPQZGQDoUlMx5GqF70Jp8ROBe5tm4UlpUCh3a/V2VFR6W/NIN9mi7idLMv1CU94dDYOe62d87dzRZQcLb3k5+hRL0tdjO5pQQVNzr1yWbfs06jbLtn1K5iDtOwpUVSZUeEej7lvNZZB24lhUVSUYVGKy1CSqhp72YqOJ/7226D61/ZnaoyVZxE/18g9AUZEMBuQoMT0NxU/CLJuhiu7NFDXtSEKlNBQ1eCQ/UzDJ/NztSFy9e9FFF/HII4/w0EMPkZaWxvjx4/nLX/7Ciy++yIMPPsjw4cPbu53djlCgc8YpUxr5XK314se1aWODrKDJRcjlZaoPdg4RslolKt+Pv6pSS4onyxFB101NcT+aIlvjIqemgj5abhO3G1/5gQ5odcehqirVn3xMya3zqVn3A71mnBN1u2RNqBmy/Oh6ZoctPkfj9LvwGiQMOVpAdDK5vgJ2O+7tmhhPPXFMq/ZNVA097769oKoYMjORbI2tKAD2HE2QuZOg6G+g1oF9lZaMTz4qsV8ISa/XIuRVNSFjqqqq4Tw/ilwfhN3JVeWPiB9h+WmSCy+8kFtuuSVs4bn99tvxer3ceeedBAIBbrnllnZtZHfDU9og0HlC49gpc78i5BQrisuZ8ODhpggFO4dyfoQwF2kzARMlfkLxPqa+heEkXqqqNqrn1RShIqcNg54lne6IqOtCri9/dTVlDz/IoVdeQvX5OPjF1+TPPZ+Ci34StiborFYKfnohBefPwZ3AWcBNEZrmnto7H6sh+kw7qyGFFIPlSL6f3ckjfurWfQeqiqlfEYbs7FbvH6qh15nfWSjY2dyvkHMGTYm6zYixWi0nb9k+FG9i60bUfLIC1efTEjDqoxfolCQpHJidENeXomhJiNDEj66Zul4dRUO3lxRyuR3D4ieugOevvvqKuXPnYjabAejTpw/Lli2jurqarCSaRtpViQh0juaf1ulIGTacurXf4NzwY8SMpWThiOWnafGTiHpYrnA9ryMurwrXIaq9NeglHQMzipraFYB+6Vqyw8OeKmp9daQZtUB0c/8BuLdtxb1zJ+lJWMTvaGrXfMPBF59HcTmRDAZ6XPATMk6bisMVIGfGTPpccD7+Gjv6tFRcBw4m/TR3KSuLc2xTIoJvQ5wzaAoerw9T30Jq167BuzeJxM/aIy6veAjV0At9Z76aGgxpabgOVXbYdxZObtinkHOHnIWqwgfbI4PMZwyexjrbcoIOB959exM2RikeDzWffAxA+imn4GlmuJEMBs3t5fdDExaijqJhdmcVqdNdXnC05afeDSjETyS/+93v+Nvf/sbs2bPDyyRJEsKnHYgIdD5lSpPbWUccR93ab3Bt+BHOndNJrYsNVVE00zhgPsryY+rTF3Q6gg4HgeoqDFmtf9ttC9Hy+2yun+JenN4PYwvp7S16C7nWHMqdByl17OG4HlquJUv/AVST/Jmegy4nFS+/RO3qrwAwFfaj15VXY6xPSx8MKtQFwenzUvv1WireeB1TcX/yr70ukc2Oiqqq4bpecnpPzh18Iqqq8sH2zxrN9nI6/GEhnixur2BdHa6tm4HWu7wijtPgO7N/spLD7y0h5bjjybv8ivZqagQhy5mxT1+cDj8jc4dw7tBpOLx12EypuD0+XLUBzP2KcK7/AU9JScLEj33lZyhOJ4acXFKGjcBTfbDJbY/E/XR+zKoaSnAYY3bnjiA820tVG7i9kjOsoj2IS/zYbLaw1UfQvjhWr0b1erRA5wazkY7GOkKbUu0pLSFYWxvVQpQo/AfLUX0+JKMRw1FVtGWjEVN+Ad49u/GU7OpU8ROoqdGy0koSloGN432GtuDyClFk60u58yC77LvD4sdcrGV69u3fT9DlRJeS+LIvkiQhyxKKomqFXDdvovyZ/2o5jiSJrBmzyJ45O2oeFlVV0eX0IuBwoGzflpRFKoMOB6rXqyX/zMzC6fAzpMdAzh16Fg5vHemmNHy+AE6HZgEx9dHcXv6DB1E8HuQEj2F1674DRcHUpy/GnNYX1Dwa7TvLI+Bw4Nq8qUMsq4pfm74OYOrbj2BQ4dGvnsWn+skw26jxOLh86M8ZnDXgiPgpTYyLWw0EqP7oQwAyzzqnxftXNhgJkiC3V6ioaaiuV0IsP1qUkap9qG+XsPxE8Otf/5o77riDkpIShgwZQkqUrLZjx8Znxu3uhFxe0QKdG6LPyMSYX4CvbB/OTRuxnTS+k1rYMp766cSmgj5Istwo4665qKhe/JTEbe6Ph5DLy9Snb1icBJUg26u10hQtBTuHKErvy1cH1kQEPettNgw5ufgrDuLZtSsclJ4IdDoZiwFMZiMBpxN9mpXa0t3sff1lzdqWk0veFVe1+DZu7tsXyWRCcTrxlZVh6pNcxQlDVh99ZiaywYA/EODeVf/CYjCTYbahKvCXsb8Pb69PT0eXkUGwpgbv3r0RAjgRhGZ5tcXqczSWgYNApyNQVYn/0KF2EVUN8ZWVQTCInJqKPisLT8BDpUdLMplr6Umtt46yuv0MzhqAKRQHl6C4xNpvVhOoqkJns2GbOJGWbBghy4+SAPETrugezu7c+ZYfSZKQJZmgqoQtUMLtdRS33norAA899BBAxEM69LaxefPmdmhe98JTWop3d2mTgc5HYx1xHL6yfbg2/phU4iec3LCwMGrG3ZTi/tg/+7TTB8Uj9byOWNRKHHvwBL1YDSkUpMVWgToU9Fxau7dxssOKg7h37kiY+GmyRMWMczjurtspffs9bGecFZHcsSkkvR7LgIG4Nm7AtW1L8omfUE2v+mru1Z4aAkoAp89FrVebzu7yu0hpEAht7luIs6YGz97dCRU/QZcT56aNAKS1o/iRTSYsxf1xb9+Ga/Omdhc/nlAl9/pZnAecmhsp3ZjGoIz+7KgpoayuXNumvsaXv7y800u/qIpC1Qda/FfmGdM0q04L7qywBTQYRA0GkToxuV94ppek2V7kBFh+gLD4UaT6chfC7RXJCy+8QF1dHan1WYcb4nA48CY4ur+rEg50PiF6oPPRWEccR/WHy3Bu+DGp3BKhmV7pg4obpb4/Z9AUzjxuKAfQcoB0ZrtD8T4Ng51DLq/BmQNiHnDyrDmYdWY8QQ8HnAfDoslSPIDar75M6IyvJktUvPEWSBIF559HnTf2tznLoMG4Nm7AvW0rmVPP7Igmx83RNb0OurTPuSk9Cah+DrmqKKsrZ2DmkVqDpr6FONf/kPAZX84ffoBgEGPv3uF4q/bCMmQo7u3bcG/ZRMapU9r12KF+C1Vy3+/UhE7v1F7k1/8OyuoTgOrTbOizswlUVuLdXdqptQid63/At78M2WIhPdaaVzqdls04GNTKcnRmZuNQgsOQ5aeZBIe/+92vcTqdPPPMS1HX33vvHaxb9x0jRoxk2bL3ItbpdDoyMjIYM2Yc1177RzIztQoBd965oNG2JqOR3rm9uPBnFzN7dtNxpd99t5Z5834TsUySJCyWFIqL+3Pllb9hzJhxUbeVJAmz2UyfPoWce+75zJ49p9MmwcQlfi699FJef/11Ro4c2Wjd119/zR//+EdmzIiee0IQnchA5+izhY6O4TAPGIhkMoVnVCRDGnlVVcOWnzXSAd7auCa8LpRxl6EKfUwmFI8HX/kBTL3zO7xdAYcjnJjNMrCx+InV5QX1yQ5tfdhSvZ0Sx56w+DHXV3j3lOxKiBhtsUTFe0vpc+HcVpU7SBk0hEq0xJCJmJ3XHEfEj2b5qXAdBiDX2hNZL3HIVcV+Z2PxA0cEeqKo/Vb7XaR2gNs3Zegwqpa8g2vL5nb/zsL1+gr7AbC/3srTy5pLvrUXAAecB8MWUXO/IuoqK/GUlnSq+AlZfdJPPa1Zi5Mka7EuiqogSzKywYASDGpxPzFYR9uLcFHTUHbnZl7EZs48l9tv/xu7d5dSWP89hPB6vfzvfx9zySWXU1pawogRI7nzzvsi1m/YsJ5//ONe7HY7DzzwaHjdiBEj+eP8v+AOeMiUUwiUH2L5qs+47747SUtL47TTzmj2Gv7zn+fJydGS2KqqyoED+3nqqX9y441/4JVX3iIvr1fEtr1798LvD+JwOPjii895+OH7KS8/wK9//X+xdVobiVn83HTTTRyoL1egqioLFiyIavkpLS2lR48e7dfCboLjm/pA59w8LIOHRKzT6WQMZimicrJWsFEmZchQnD+sw7Xhx6QQP0F7DcHaWpAl3q+NnoF62Y7P+UP/Ymo3bcZTUtIp4idk9THmF4TrpLn8bnbXarPShmTGFuwcol96X0382HczOV9zOZryC7QYGbcb34H9mPIL2vEKWkaWJQLOWEpU6AkGYxM/5qIiJIOBYK0D34EDmHq3r5WiLYTdXiHx49bEUE5KD1IsJr7b/yP76yKTToZKrXj3l6H4/Y1qPHUGisetzdIE0k5oP5dXCEtxfySjkWBtLb6yfZgK2sddqQYCEclL4Yj46Z3ai2xLJiadEW/Qx0HXIXqn5mni59u1neridm/fhmfHdiS9nswzpjW5nayTqPE4cHhqCaoKOkkmUyehIwFBz/WBxYEYsjtPmXI6Dz10H8uXL+Oqq66JWLdy5ae43W7OPnsGTz75OHq9nuzsyOdx7975lJXt4+mnn4rw4Oj1erJ79KDO5yRDTsGoyFx2wc/49JvVLF/+QYviJyMjM+JcPXr0ZP78v3PBBTNZufIzLrzwokbbBgIKPXr0pLi4PwaDgSeeeIxzzplB3779WuiwthPzq+lZZ52lZaFs8MYY+hz6k2WZUaNGcffdd3dIY49lQhmd0085NeJNTaeTsdoMLNu1gqvfuYmr372Jq9+5iWW7VmC1GUitt74lS6mLcA6Q3r1wqJ6o2zj9LozF2uDZWTNB3FHy+2yr2YmiKuSk9CDb0roCseFMzw3KXEg6XTiPUSLqfHVEuQNJrz9Su6y+D5OFUMBzyO0Vtvyk9KRvuiaoQ26ZEPqsbOQUKwSD+PZHqUvVCTjXr0cNBDDk5mIsaH+BLOn14ZI4ri3tF3vpO3AANRBAtljC2bJD/ZtvzUOWZPJTtbf7kOg0JyDouWqZVuU8bcLEcGmdo5FkqPE4qHbbtQBfVSXg8eD0OlF8PoIuJ4rX2yl/DbM7h+t6NRPwbDKZOeOMs/joow8arVu27H0mTjy5keA5GqPRiCRJ6I5y7YUTHYaKmypBdDodRmN8Lwkmk5Y6RB9lRunRzJ59Pnq9nk/q8zJ1NDFbfk4//XROP13znV5yySUsWLCA/vVmfkHbaBjonD7x5Ih1BrPEO1s+bFQ5OfT59BOP5+CL2sM26Haj6+TkXEcTKhyZWlyM1bAvaskBqyGFjMFDqHzvg06r8O7a2ji/T9jl1UqrDxCu8XXQdSgczwTaW7d7y2Y8O3dCM3maOoJwuYOZ0yNifkLEW+4gZdBg3Fs24962lYwY4yc6GsXvI1CtzTI64vbSxFCeNYe8DC3n2P668gjXjyRJmAsLcW3ehHfP7rD7pjMJu7xOGNNhbsSUIcO0QPUtm5u1frSGULBzqGSNw1dLnd+JhESeVRNDvVN7scu+m311BxjDaEz1/RuorCRQ60CfFr1uXnvhLduHc/0PWiqHs6Y3uZ0sSTg8tUB9vqjH/oNaugcfUNOhLWyMecBAev7sF0gQDjRuaar7jBmzWbx4IRs2rGfECO0FuLLyMGvXruauux5ocj9VVdmwYT1vvPEqp556GpajnhdyA/Hjcrt556MP2L27hKuvviba4ZqlsvIwDz/8AFarlckxJH5NSUmhV698duzY1upzxUNcMT8vvvhie7ejW2Nf+SkAqSecGBHoLEmaq6u5go1zzj0HQ24u/oMHcW/ZROroEzu+wc0QMosb+xRwzqABTWbcNaT1DW/f0e6HYF0dvrJ9QORMry1V2o+sNfE+IVINVnJSelDhOkypYw/DszVRZR5wpMhpInD7offsmaCqHHh/2ZHZXrNmUHD+HOzO2Mz5DePLQn3m2rY1aeJ+Aoc1K49kMqNLTcMf9FPlqQE0t1evtJ7oJB2eoJcqTzXZliMJWE19++LavAnPnt2kd3K7Fa8X54/rgfizOsdCytChALi3bmm3mUuhYGfzUS6vnpbscHLQgnrLT5lTs/zoUlIw5OXhLy/HU1JC6sjj29yO5qj+YBmgjaXGvLwmt1NURateHiKRt7SqamUkJAlF1gRIS7+xoUOH07//AJYvXxYWPx9+uIzMzCzGj58Y3m79+nWceebk8Gefz0dGRiZTp57JVVf9NuKY69ev4/zp01FRQVXxer1k2NL5zdX/x6mntvzSc8klPwm3O5RZfNSo0Tz++H/oUT8jsyXS0lKp66TCw3GJH0H7oXg8OL6OntFZliWcPlezBRtdfjepx42k+uBHODf8mHjxU2/5MfQu5Nwho0CFZQ1T3w/UMu7W2X3oUtMI1tVqOVeKi5s/cBtwb6+P9+nVG71Ne/M87K7ikLsSWZIZlBnfuYtshVS4DlNiPyJ+LMWa+PGVHyBYVxeOL+os/B4PG26/h74/vZBxzz1NwOVCb03B6/bFVO4gWnyZ4bhBlOn1BGtq8FdUYMzN7aSraRpfg3gfSZI45K5ERcWiN5NmTEUv6+hlzWFf3QH2O8uPEj+hoOc9UY/dkTg3/Ijq86Hv0QNTYcfF6Jn6FiKnpKC4XHh2726X31fYpV149EyvIyIj5PYqqz0Sa2XuV4S/vBxvaceKH39lJY5vtLE06+ymrT6gCQxd/bRuSZIwXHsV+PyASs+aAJIKxt75Mb2U6fUygUD8+XBUWcZftk8TPxIYYpx1OmPGbF544VnmzbsevV7Phx++zznnzIxwZQ0ePJRbb70DgNLSEh566D4GDhzElVde08jqM3jwUG665a9Ueqox6Q3keXVkWFPDsxHLy8u55JILI/b56KOV4f/ff/8j9OyZg9Pp5KWXnmPjxh+57LIrGTgwdst6XV0d2dmxCaW2IsRPgnF883V9oHNuo0BnRVFJM6ZgNaQ06T5KMVhIGTaC6o8/wrlxQ0LfzIMu15Eg1N4FOB1+xuWfwOwGqe8P2CtwOvwoioq5qAjnj+vxlO7qMPEjSRLBw4fQ22xRrT79bH2x6ONzFfaz9WV1+bcRRU51qakYcvPwHyzHvWtnh7/pHo1r40Zcu3ax48n/UHzfg+j0ehR7bLO7QvFl72z5sFF6gsEDB1C3eQvubVuSQvyEZnoZw/E+9cHOlp7h+793Wi/21R2grK48nIkbjlguvHv3dPqsvLrv6mt5daDLC0CSZSyDh+D8/jvcWza1+felKkqDYOd+QMOZXkfET+/6/9t9Dup8TlKNVsz9iqn9+qsOi/sJWSkrV34KwSCWIUPDsXdNoagqNnMa1W57+BjUx6fIKUYkfwBJlmPKhyXrZWRd/OInVPhVy+4ce12vadOm88QTj7FmzddkZ/dg166d3Hnn/RHbmEwmCuoD3gsK+pCfX8DVV1/KggU3c++9D0XcgyaTiT59+mJwmrXg71oV1ecLJzrs0aMHzz77SpPtycvrRa96obRgwZ1cf/3v+NOfruPpp18Kt6E5XC4Xe/bs5swzz47p+ttKciSG6cbYP/8M0Kw+Rw+Gqqri8fo4e+CUqPuGCjZaBg9B0usJHD6M/2B51G07g1A9L31mFrq0NIJBhTfXL+X/3pvPk9+8yP+9N5/nvnsrbH0IDVDeDoj70elkUs0yWekmCs6Ywpj/PEHhT85Hp9Nu+XimuB9NUXp9skPHXq0YYD2W0JT3BNT5CmcNPuFEkCSCQSXmGJ+G8WUhsR2KL9ufqz0YXPWz5hJNU9Pcc1KOBHrm11skjp7xZcjNQzIaUX0+fOWd93tR/H6cP6wD2jerc1OkDNFcX652SDjrP1iO6vUiGY1hd9KRmV5HxI9Zb6aHWbOylYWCnuuTHXpKSlodb9YcDX/jVsnPwEsuYshfbiL3/Lkt7qsoKummNDIttrDY0EkymZZ09Cat7ElnzfgKTXMPlZSQm8nx05CMjAwmTTqFFSs+4uOPlzNq1AktioyiomKuuWYeX365infeWdhova5BcdPwS0F9MLZer6egoE/EX1PodDpuuWUBkiRzxx23osSQKfrddxcBMHVq+8SotYQQPwnEs7sUb2lJ1EDnEH6PyoxBpzN32DnhoFqrIYULhk/n3CFn4feoWlbX+tw1iZz1Fa2Se1ndfmq9dYzIHUytt45d9lKC9T+mcPr7kvad8RXKclyxZAnfXHoF3171G9b86mqqPv+cdKsBSYat1ZowGdoG8dPbmotRZ8QT9IQT7AHh2VGenTvbdiGtRA0EqPvhe6D1D9eW4su+MGiZfENZshPNkZlemvg52GCae4jwzKOjZnxJsqwV2IVOrfDu2rQRxeNBn5nZomWiPQjl1XHv2Nbmkg1HKrn3RZJlFFXhQMjtZY2MrTk62aGpT1+QZYK1DgJVVW1qR4ijf+NrL7uCNb+6mrqdO8kbNSz8ktMUdT4n+2vLMetNFGbk/3975x3mRn2t/3eKetveq3e97r1ggxum2MY2YEMg+YVcOlzgJrnkhkAI5OYmEEgCpEEIpgQIkEDA9BqqKcbYBvey3d7e1fvM/P4YzUjalXYlrXal9X4/z+PHtjTSfjU7mjlzznveg7KMIpRlFMOkMoBix3fAqezuHAh+4hltsWnTBfj880/x8ccfYNOmC2J6zZYtF2PevAV4+OE/oyeQqZeQBM/ifK/AvxOc75Wbm4f/+q8f4tChA9i+/YWw58zmAfT19aK3txeNjQ149tmnsG3bX/Af/3EVisfJIoQEPylEyvoMFjqH0mnrwZ0f3IcpmWXYdsG9eHDTXXj4/F/jrIqV8sBGANAGBp2mNPiRZnoFLiw+3o9Op/jlWlm+FFpWAw/nRWvgpCjdEXo7O8A5I+uaEiHU5VjyvOEcDrQ+/y+0bn8ZDO2F0++CmlGj3JC4BwpDMyg3iF/U0NKXpPtxNTaO62wc5/Fj4J1OMAYjNNXxBXUj6csaM/ngzKjenojbjCdRDQ61Qb1AsUEMfrqcPfDx/rDXy7qfcXR6tod2eY1DqU1ZWATGaITg841agC+LnQN6nz7XALy8DyzNIlcTPpy4OBAMSWMuxGHGovVAsqwton7HX3gRrdtfgWYYQYcgCLB57fByfnh8Pjg8LnTaetBh7YLAA5RCfPG4zfiSJrpTUvAT+7GxdOkyaDQaWK0WrInVyZqicOutd8Dn8+P+++8Ne46maNCBdUjzvTCKc9imTRdi0aIleOSRv6AzJMt67bWXY+PGc3Hhhetx/fVX4osvPsPPfvYLXH319Qn/rHghmp8UwbvdsO3aCWCo0DmUz9t3oc3WiTePfoxKdTX+efw17O85gvVlZ2FNaXD+l272XPT+63m4jh8D7/WCVirH+iMMYbABWqejC7zAQ8tqkKPNQlVGBQ72HkW9uQnlxlKwBiMUObnw9fYkzf5+RJfj199E8UVbYFDpMcVQPqyNfCxUmspRZ25Ek+UkTi8SLdyVxcWg1WrRwXocB4LKJa8FC+O+uI6kL1NpdNBVZcBRWwdXba08TysVCIIQMtdrkOYnJPjJVJmgYTVw+V3ocnSHzW5Tl5XBgmBGY8zX7PfDvi+xrFysDHaApygK2ukzYfvqSziPHZXLYIkgZ34kvU+gm6tQmzfkOzQ48wOIWV5PSwvczc2j7nKL5TteevHWqE7mbs4DH+8HTVHQKbTgBR5ezidONBcEecCp4PONi4ZSdncOfGXjmetF0zS2b38z4nM/+9kvor6urKwcH374ecRtaYoGL3ByMCaMMN9r4cLF+OyzPVGf/+MfH5b/XVBQIG87WqH4aCGZnxRh+2oXeHdkobOEn/fjyw7xQFlRfBoEQUCuWpycfKgvvI6vLCoCm5kFweeT3YzHE8HvhyfQTq4OZH5abeLJr9RQBIqi5DEDDeagxifZpa9YXI49disy1MZR6X0kKgJmh03W4EWUommoK0Xdj2ucdD8Cz8P+zdcAEru4unxu1PY2Yv3UyH4cG2rWQDtdanlPrdkhZ7VA8HoBioIiJwdOnxN2n/j7ztUEy14URcklmcGlL8l/xnPyRFJ1KNFwHjsqZuWM8WflRoJhaKh1DEyZatAaDqZMNdQ6BgxDyy3vozE7FAQBnhPNAIKZn3a7WAYt1A9tJ5fa3aUxFwCgrgjo+5Igeo7dyTxy0OIIHCt6hT7Q9cWApigIELPVUtkLPD+qrEesSMEPJ7s7j/9E91Dk0lcSMj/pDAl+UoQ5MMQ0ktBZ4kDvEdh8dpiUBszOFk9i0t91Aw1w+4MDZCmKSmnpy9vRDnAcaI0GbGC8iSR4lO64peCn3tIkC4RDxZDJIBaXY6XeALPbmpTgpzJgdtjp6IbL75Ifl+Z8+drawDAj+3aMFlddLTibFbRWB22UYDrqa/1uPLT/cTy29x/YMPVMXDzzvIj6MnWVGPykWvcjlbzYzCxQLIuuQMnLpDRCzYZ35wRFz4OCn6JigGHAO53w9/WO+ZqlLi/9gkVJLXmN6AA/SzwnuJsawbsjO66PhK+nB7zLBYpl5bZnKfMzWO8DAFlqccyFX+BkLZz8PQ8MMx4No3Ey9/OcnOUxKMXXUxQFBS0GPD7eB4qm5Qnv41L6GuTuHE/ZayyQfr4QOGUlqvlJd0jwkwLcJ0+Id0AMA+PpZ0Td7rM20bNiedFSObWcr81FjjoLfoHD8YG6sO11s+cAgDw3aDwJE0QGLvSStkcKfsqMxVDQCjh8zpCTohgQJasNVnY53hx5sG7hpvNwqOMoFJQiLEuQKEalAdnqLAgQcMLaGnx8zhxMv/1WTLv+KuhpH7JMKuhV9IhCzESRS17z58sn7lhw+V14aN9jaLQ0o99lxonuTmyoOgvbLvgNHgroy9aUnwGH1QfllGqAouDr6YYv4K6cCobqfYaKnSWkTiTJdE+CYll5ppx7jP1+BI6D/WsxK2dYPHzJRxw5EHuwPFyH3qvH3oWuNE+8GeE4uOoSc871BJydlSWl8rHV7hAzP0X6wiHbRxpzoSoqBqVQgHe54OvuHvKaeBjxOz6Mk7nbLwaAWoUGLB38nigC//bxYrATWvoaa6TMjz+G0RbjgZT54aXgh2R+CMlCmuNlWLgoqt17t7MXxwfqQYHC6YVL5ccpisLsHDH7c6g3PJWtnTEToGl4OzvgG4e72VAG630EQUBr4MRXGgh+WJqV28PrzWKZS11eAVAU/AP98JuTc0F1+YDiLRei5JKL5btDRqdDybcvQf6W8/H04VcxPXNq0rIxUvZHEj0zDI38+bNgr2/A7quuxe7Lr8ZXl1+N7jffgEmnSHoAJJa89gIQxbSx4vQ58advHkWT9SS0rAY/WHAdCjQFcDs4WAbceH7/G7jpjTvwRcPX4DgejEYj/35TOedr6EBTqc19qA6pSCddhIe2tEtmfdLFfaxw1dWCs9tA6/VhXlOhDFe6ioaTc0KlUgzrAK9WKaELaOmcR48ktH73ILGzj/fLAWeRLrLnkxQUSecAimXlRohkiJ5dPqD4wvMjfsdLtm6Byz/0NVavDV5ODGYMyvAGEwUTyPxwg4Ofse/4Ck50F//PjKPvVCSk4EtaD0bQ/ExUiOB5HKEoCpTfC9eRQwCGFzp/0f4VAGBGds2QoZuzc2bg49bPcbjvGHiBlyN1RquDekoV3PV1cBw6hIzV0d8/2Qzu9BrwmOHyu0BTNAr0wRNktakCtQP1qDc3YWXxctAqFZRFxfC2tYr29wviGzAaCY7j0frBDhiqqrDkb4+Cc7lll+P7dz2BNlsn1pcPP6E4HiqN5djTtQ9NgSGnGgXQtv1ltL7wYnBNDgda/ym2e+Zt3AR7Es8n7qZG+AcGQKnU0M6aFdNr7F4H/rzvUbTa26FX6PD9+deGCYIFQYCKUsPmseOkrRVn4DQA4pwvz4lmuGqPw3ja8uR9iDgIZn7Cxc75kYKfwLFn9ljg9DmhDZTzAClQ/3TMnZ7lWV7zF0YcMzGcueQF09fBYfVhwGVBi60NLbY2nAz8rVNpcOuKG0Z0gNfNmAnLpzsS1v14Bomduxzd4AUeGlaDDFXkASHymIsQjyV1RSXcjQ1wNzfBGDKCIRE4jkfdtieRd9qSId/xaE7mezr3oYTOhoJWQMWEN4QEy15i1DRemR9BGm0BUfBMUQCV0lkbocNNxf+nW+YnWRo9kvkZB0LNuPQKYOGDf8CM/70T+igXKj/vx84O8YS5omjZkOerM6ZAyShh8dpkUbFEKkpfgiDImR91WbjYuVCXL6eUAXHtAFBvDhqeJbv0BQC977yNY/f8Bs1vvw87z6Lf4kGrdQD7uw6DAoWazOQN5ZUyP82WQAA4QieKSqNMqgZI1pPMmwdaMXKXn81rxx+/eQSt9nYYFHr8cMH1YYGPRKlBLAudtAWnn0vi/FTqfgZ7/EQyOJTQsBpkqcWAum1Q9kdyeh7Lji+B52H/WszKGaII0YcrXb1y9B2ccDfhp5/9Cn/Z/wReb3wX+3sOod89ALPbCpPaIOuzBiM5wGsCXV6elpPg4pybJIqdwzM/7SH+PtGO4+JIwU8S9X2etjb0f/ghjt37W3Q3tsnfcbuHjxj4eDkvdrTvBCdwUGPoyArpHOXn/aLB33iVvXhenO0FMfhhKCbls/PoIZPdYzdKHQ+8XlHryjCjy92QzM8YI5lxtb60HR1vvBUcNLnpPJTMmhnxLmV/zyHYfQ6YlEbMzh4qXlXQLGZk1WB/zyEc7DuKMmPQFEo3ew76XtkO59HDEPz+uPQfieLv7R0iiJROesWDNAGVpjLQFA2zxyIPnFRXVsL62Y6kdXx5Wk6Kd6sMA928hfL+lVydSw3F0CsiiyUToVhfCAXNwuF3wuwzw+QwxNCJwoLjRn9CEQQB9r2xl7wsHhv+tG8bOh1dMCoN+OGC61AQpXRRFvAward3wM/7wdIsNFNrAIqCt7MDfosFrGm8R4OGzPXKyQMv8BHb3EMp0hWg3z2AdkenLLoHAFVJqeiCbTaP2WdxN9SDs1hAazQRrRxGMpd8p+4TXDBjHYwqAzSMBqWGIpQZSlBqKEaJvgheL4cNNWuiDhB2e7xgjCYoi4rgbW+H8/jRuFrN/QP94Ow2gGGgDHj1RHJ2HkzkMRdi8ONpOTnqYasD770DQLR1YHNyR5xZt6tzL8w+KxocJ5GryYGdUUKpVMmBhiAIoAIWAW6PE6xAww8B8PtAedzDitR5nkr4u8z7vOLPoSkInAAaAnzjZK4YDYHjAI6HT/CJaxME0F5P0r2p4t1vgiDA6/XAbh+ARqMHPcr1kOBnjAk145KQDPdAURFLIJ8FSl6nFy2J6kMzO3sG9vccwuHeY9hYeY78uKqsXB4Y6mpsgDaKxiCZSHfOyqJiOdiSxc768IyCklGi3FCCJutJ1JubAsFPMPOTDF8Nyxeif4V+/oKwwaLJGGkRCZZmUWooQaOlGU0DJ1GVuxSMThcxAJI7USyeCO8UP56Wk/D19oBSKqGbM3fYbc0eC/74zSPodvYiQ2XCDxZcF7FUJJGjyZJ9ctodnSgzlIjdcsUl8La2wFV3HIbFS6O+fizgvV5wZjMAQJmbC4vHCi/vA03R8liFwRTpC3Co7+iQMRe0Wg1Ffr44dLPlBFjT8PsvEcJKXhFuRGIZXuzyuXHXGT8FE+F07XMLuGD6OgCIWjIDxFEX3vZ2OI/FF/xIWR9VUZGcVWyP4uwcippVI0eTjV5XH9rsHZiWVQ1FfkHQ/6q9PWH/K7/ZDOuXXwAAMtdtGHF7XuDxYYs4gDPDlAutVg+7fai+0OWxwc/7AacHSloJv9MCCALYHoBiowdqNE3HNL4h4tp8PnAOKwSahp0DlIwClHOczBWj4OP8sHttYCgGfoe4FraXApVkrWKi+02j0cNojPxdj4e0Cn6ampqwdetW3Hnnndi6dSsA4OjRo7j77rtx6NAhZGVl4YorrsB//Md/yK/heR4PPvgg/vWvf8Fms2HJkiX4+c9/jtJxMpYbjkTMuLqdPaiVhM5F0S8s0hTxE7YWWDw2mFSigI+iaWhnzYZt1044Dx0cl+An0liL1iiZHwCoyqiUg5/TChcFO0GcTvi6u6DMj35SHQnB74ctcGI0howM4QUexwLdcTOyYp8yHCuVpjI0WppxbKAeK93zUbh5o6zxCWW4TpREkLq8dLPmDBnCGGp61+fqxx+/2YZeVx8yVRn44YLrkavNjvSWYa8vNRSjdqAeLdY2OROkrZkGb2sLnMfHP/iRSl60Wg1ar0f3gDhCJEedFfVGoTiK1w8AqMsq4OvshPvECehmJzf4EXg+mJWLUvKKZXixXqkDR7kjHjMcx8Nh9WHDlLOwZcYGmN0WGFR6WJ2OcAf4GTNh/vADuOKc8zXY3BCILfMDiN99Mfhpx7SsanGsSHkFXMePwd3cmHDwM/DBvwGOg7p6KjSBUTLDcaTvOLqdvVAzaiwvWgw1q4bBkAmOC1dF72w8iK+792NF0TKsLVuJjpdehqelBbnf/k7UY4NhKJhMWlgszoSyP45DB9Dzz3/AU5iF5xcB83Jn44LCkQO6saTb2YN/HvgnNKwGl35gBW+zofCm/4Iqb+i5PFES3W8Mw4464yORNpofn8+HH//4x3CGjDkYGBjAlVdeibKyMrz00ku46aabcN999+Gll4ID2f7yl7/gueeew69+9Sv885//BM/zuOaaa+D1pjZ1CCRmxvVZ+y4AwKzsabJWIRImlUG+GB3pC++8kXQ/4+X34wlpcwfEdtJeVx+AoZkfAKjOENPfDRax9k+xrNxFNNrSl+PQQXA2GxiDEbqAxwkgnrBtXjuUtELuOEsmlcbAkFPLSbh8QMnWLSj59iXhnSiXfitqJ0qiyC3uixbJjw3tHFLBxdigYhXIVmfh5oX/OWLgIyGN7zhpC7bxa6YF/H5SYKYZKnamKArdruFLXkCw86jd3jkkgJACds8Y6H7czU3wD/QPK0SPdXjxcMEyx/Fyh95LB97GTW/cgY/qdoaVgjQ10+VyZTw2BZK5odQZ5/K7MOAxA4je6SUR1P0Eg06p9JWovo93u2D55CMAQNa62KZ/fxDI+pxRvBRqVhxaStM0FApl2J8MbQb6fRY0O1qhUCih1Ooh9PWBa20bsq30R6lUQa1WQ6lURd1muD8YMEPo64PT60C/zwKWVST0Psn8Y9AY0e+zoN3VBcbrg9DXB9rhSurPSHS/JSvwAdIo8/PnP/8Z+pASBQC88MILUCgU+OUvfwmWZVFVVYUTJ05g27ZtuOiii+D1evHEE0/gxz/+MdasWQMA+P3vf4+VK1fivffew6ZNm1LwSYLwvADWoIu5BOLj/djVId4pnlF02ojvPzt7Ok7aWnGo7yiWFwVT2drARd9z8gT8FjNYU0YSPk10PC3iNHdJQCqd7DJUJuiVQ7U1VaYKUKDQ5eyB1WuDUWmAurIS7oZ6uJtG1wli/eIzAIBx2fKwMoOU9anOnBImwE4Wkui5zd4Bp1f0EsnbuAmlF2+Fz2oDq9PCcugwBixOCEny8fC0t8Hb2SFqm+bOBxC9c2j91NX45Vn/g75+G3Ssfvg3DiGi6DmQTfS2tYKz28NKi2NNLNPcB5OvzQVDMXBzHllnJiHP+BqDji85MB1BiO5zCzivZi0AAe/UfRK1dDUSgiDAoDDC5rGj3tKMtVglP8fodFCVV8DT3ATXsaNQLI/tOyZlfqTvtuTsnKEyhXXORSIY/ASbMkYrerZ8ugO80wlFfj508xaMuH2rrR21A/WgKRprSqJ7qgFicwYAeWCrslBcv7ezI+prRovfZgMAuNTiRd2oHL/vUjR0rPh7FSAAWjFYjHYDP5FJi+Bn9+7deP755/HKK6/IQQwA7NmzB0uXLgUbchFbtmwZHnnkEfT29qK9vR0OhwPLlwdbbo1GI2bOnIndu3ePOvhh2aFRpuS7EatXi9fjG7YE4vX4wDAUAArfdByG3edAhsqEefkzR/R7mJc/C281v4+j/XUQaF6+qLNZGVBXVMDd3Az3sSPIOCPyxPhk4LfZ4B8QJzVrK8rBsDQ6nJKzcyFYlh6yz4ysHkX6ArTZO9BsO4GF+XOhq6qC+f1/w3OiKeJ+j3Ut9v37AACZq1aGvY9kCDkrZ1rC7z8cOWwmMtUZGHCb0epoxTRVNdwc4HF4AbBouOU2uE+2oOA/rkDW2tgGEI50rA1I3j6zZkNlFE+aoZ1DEg6fEy8deRsUReG8qrPgc8eeZp6SKZYm2u0dAM2DpVmwmRlQFRXD094GT0MdjCFZp7GG6xODH1VeHliWRk/A46dQnyf/XgfvNxY0CnV5aLV3oNPVhXxDMFDSTakAIHoHUV43GO3wF/RYEQRB7sIzLVk67DHX4+zDw1/+Df9v7gXYdsFv4PS5oFVo4PF64Xb4QVGRz0WRmJZdBTSII2QYhgrTz+lnzhSDn+NHkbVy6Dlh8H7zm82ivoqioKusAM3S6HKJwU+xvmDENZWbxMC5w9EFihbA0Ax0AedzT1sraN4f1wxCgeNgfv89AEDO+g1QKEe+fH3cJt4MLcyfizz98NnOUpMY7PS6+sFTHDTFYtba19UZ9bPGez0YjGCzAgAcavH3ZNIYx+T8FA8saGhZDZx+F4RA8AO3M6nrGu1+SwYpD36sVit+8pOf4I477kBhYXhNsbOzEzU14fqMvDzR26Ojo0OeEjv4dXl5eWETZBOBpilkZkbvCDIaNTG/V+lFW0ABaH/9Tbnbq2jzRpRctAW0UonA4YWd+0Rx5NnVK5CTHdn8MBRTRg0y9hthdlvR6WvH3ILg4MKcJYvQ2twM7/GjyNy0Lua1xov5hDi7Sl1YgJwi8aLSXS9eoKbmVoTtw9B9NrugBm31HTjpbMFZmcuhnj8LbRAN1UwGFegEutTaP/8E4DjoqqagcG5wX3g5H+oC88ROq5iLzIzkdXqFMi13Cr5s+Rqd3k4sy5wX9lzR+nPRuO1xDLz9BirPXw9aMbTdNhrRjrUT+0TX4ILVZ8j72c/7hzW92zpzA/TDjbweREaGFjqFBg6fC3baispAMJQ5dxY629vANTcg8+xVI7xL8ugwi4G2qaIEmZk69LjF4Kcqv3TI9zV0v1Vkl6LV3oF+ri98u0wdTuTmwNPTC8VAN0zFsfkkjYS9sRG+nh7QSiVKVi0Do1ZH3fbD9k/QZuvEu/U7sKRkPkyMqN9TaFgg9tMMAGC+cRqUexWw+xxwsjaUGEPOjUsWoO+tN+E+fhQZGdqojQXSfutvEMvpmuJiZBeI2bLexsD+zi0b9vwIAKYMDdSsCm6/By7WjlJTEYQMLZqNRvitVijNPTBMi11/17PjU/j6+qAwGVG+8VwwgzRugxlwWfBVpzhMdsvsc0dcb4Yg6qvsXgecjA3506rQAsDb2Tns/gLiux6E0ukWZR52lXhDUpSVM+I6xwOT2gCn3QXKIB63Ss47JutKdL8lg5QHP7/4xS+wYMECbN68echzbrcbykF3BqrAAe/xeOByibOUIm1jsVhGtS6eF2C1DhUgMgwNo1EDq9U1YnulBE1TyNu8GSUXb4Xf4QSr08Lr8cLm8oMPqOm7HD043F0LChQWZS/AwEBsacZZ2dPxedtX+KLpG5SqgoJjploURA98/Q36+2xJb1OU6D0iWuYrikvlNTf0iqnyHEUOBgYcEfdZqVa8iB7qrMXAgAOC2ghaqwXvdKLz4HFoKiriXkvHvz8AABiWnS6vhaKAZutJqFkVtKwGet4U876NlxJNMYCvcbijDqsLwu+slYuXg33hJXh6etH85nvIjMGAcrhjzdvdBUdTM0DToKfNwsCAAzRNQVD6h+0ccnhdgIeJOPco6ucyFON4fz0OttYiA+JFkKmoBvAeBg4cHLP9GQlnm5hV9Osz0NNnQbdD1JZpeYO8jkj7LVcpBuYNPSeHrFdZWg5PTy96Dh0DX1yRlHV2f7ADAKCbOw9WFwe4Iu8jQRDwSZOo81uYMzcp+7LCWIbagQbsPXEEupLgTRRfVA4wDDw9veiubYIyL1yzM3i/9R4WNV3K0jJ5XY19Yok7m82Jaa3F+kI0mJtxpK0Bel60ElBXVMB+4AC6DxyBP684ps8kCAJOvvgKACBj7dmwOv2Ac3jx3Kv174PjOVRlVCCHzotpvQXaPNR7m3CsvQmmvHni/De3Gz2NrVBkDe0wSuR6EIrP7YG2vAxuvQKAF/Cy4/p9ioaGEYMSJ02BBWDvHUjquka734bDaNTElFFKafDzyiuvYM+ePXj99dcjPq9Wq4cIlz0eUR+j1WqhDtxNeb1e+d/SNhrN6CNKvz/6L4Xj+GGfH4wXAOXmQdMseItniIDxk5M7AYjBjJE1xvzeM7PE4OdAzxFsrdok350oyytBazTg7HY4GhrldvJk42puFn9eSSn8fh68wMuan0JNQdjnCN1nlQZRQ9Bqa4fN7YCG1UBdOQXOw4fgqK+HoqQM8eBpbYG7uVnUvyw+DYIgloDUKiVKlQV4aNNdODHQBoCK6/cWD+UGcc2N5hPw+bjwO0WaRea6Deh5/h/oef016E87PWYPpkjHmvkrMUuonTYdUOvg9/OgKAom/fCdQ1qFBhZ75M6haJTpS3C8vx7N5hYsLxC7u1TV4h27++RJeKw2MNqxv1sVBEH2+KEzc9Bl6wUv8FAySugZ/ZB9FLrfCjTihb7V1jFkO2VpGfD1Xjibm2FKwrEhCAIsu8Xfj27BomGPt5O2VnQ6uqGgWczOnpWUY7PKVInagQbU9jXg9IKQbjxGAc2UKrjqamE9eBgZqyOLxKX95mpqBiAGh36/aHTXbhO/2/mavJjWWqgrQIO5GSct7ViYO198v/JK4MABOBsbYYzx8zqPHoH7RDMopRLGVWeO+LO9nA+ftIhdn2tKVsS8Xwt0+ag3N6HN1gkubwEUubnwdXbC2doGnTEj6uvivR4wDA2NApj105/AZzFjdoYJhzqPwaSM/dw/lkjGmR4lDRaAz2Ybk3XFu9+SSUqLiy+99BL6+vqwZs0aLFiwAAsWiAK2//3f/8U111yDgoICdA8agif9Pz8/Xy53RdomP3/4ToRUIAgCOG6oW6aP8+HLTlEfsKJ4ZKFzKNMzq8FSDHpdfbLZGyB2UEmmamPZ9TV4ple3sxc+3gclrUDuMCLUDJUJOZpsCBDQGJiJNZpOEKvk7TN3PpQZprBJ1ze8fjtueO127Os8DJ0x+bO1JEr1RWAoBjafHX3uoR01plVrwBiN8Pf2wvrlzlH9LNnVOcTYUOoc2lCzJuJrYukcikQk0TObkQFFfj4gCHDV10V7aVLhLBbRcZeioMjOlmd65WtyRvSGksS3Xc4eeYSBhNSlmCzRs7e9Db6uTlAsC93cecNuuztQlpmTMxMaNnppLB6kbsp689DvkeT27Do28pwvd2DmmdTpZfFa4fA7xZE12ryY1hJxzEV5hfj+cXzP+98VTQ2NZ6wAYzCMsDXwVedeOHxOZKszMS8n9lLmENFzQfJFz5Lxbffrr2P3Vddi73U3Yu+V1yHz86MozsxIqQ5GQq8QNYROpfi9OhUFzyndy/fddx/eeustvPLKK/IfAPjBD36Au+++G0uWLMHevXvBcUEXwC+//BKVlZXIzs7G9OnTodfrsWvXLvl5q9WKI0eOYMmS2I28Us3+nkNw+JzIUJkwMys+Xx41q5ZHRhzsGzTodIxb3nmPB94O8aQgjbWQOjuK9IWyTXo0Bp+kZbPDODtBBL9fNj0znrEi6riAl46Ik64V6rGxj1cwCjlQkIachkKrVLIpW/+br8sDDePF198Pd2MjQFHQL1wY/pxbwKaas3HRzA3y3ZtOocXFs87DBdPXxSV2lhjs9CwhdX2N16gLqdOLzcoCxbLoGsHZOZQMlQkaVg1e4NHlCL9ZUgUuxt6OdvCjtMigKAq+xnqwRiO0s2aDGSYDzQs89nbtAwAsyR+5cylWKoyii/qAx4w+V3gQLt0QOY8dHb593m6Hv08sKUrBoeTvk6vJkQeBjkSxPtzxHQh2fHk7OsC7XSO+h6etFc5DBwCKQuY5I7e38wKPj1pEofOakjOi+j9FQmrf7wh0tcnBT0fygp9Q41spqOAcDrQ9/yLatr+COCR5Y4bkgO8K/Jp5Evwkl/z8fJSXl4f9AYDs7Gzk5+fjoosugt1ux89+9jPU19dj+/btePLJJ3H99dcDELU+l112Ge677z588MEHOHbsGG6++WYUFBTg3HPPTeVHiwvJ2+f0oqVxfVElpCnvh3sH+f3MEoMfd2PDmETunrY2QBDAGIxgAu30krlhSQRzw8FUmwYFP4HMj7e9DbzbHfM6HIcPgbNawRgM0M+ZO+y4AGnS9VjNz6k0Bia8WyNnETLWrAWjN8DX0w3bV18m9DOkWVGa6qlDbAw4jsdTe7djSmYZHjn/Hjx6wW+x7YLfYMOUs8JM7+JBcnr2Cxw6HF3y49qawJyvcfL7CU5zDx9oOlybuwRFUcEJ74PMDtmMDDGbwPPwtLZGevmIhM7vK1xxGhY/+jCqrr1q2Lv42oEGWLw26FgtZmYnz4xUzarkIFzy0pLQTKkCpVSCs9ngbYv+WaUWd0VevtwBF3R2jj2rLm0rjbkAANaUATYzCxAEeWL8cAwEsj76hYugzBs543S0vxadzm6oGRWWD2MUG4nCgCFmn3sAXs4rt7v7kpT5icX4Ntmz/xJBunGyK8QbNJL5GWeys7Px2GOPoampCVu2bMGDDz6In/zkJ9iyZYu8zQ9+8ANcfPHFuOOOO/Cd73wHDMPg8ccfhyKObppU0unoRp25UXR0LkwsWzU7Wwx+6i1NcPqCd1KK7Gwoi4oAQYDz6OGkrDcUT4vk/lomf1mlsRbFEcwNByNlrE5YW+DlfGAzQk6KcZjOSd4+htOWg1EqRhwX4PS5wowlk0nFoCGngxGzP+Lda98bryc0MVkueS0Y2mLu5Xz4rHUXfvf5IzjWegKck4ZlwA23g0tYWCg5PQODzA4DmR/3ieaY7uBHizzTa4jHz8iZH0BszwaCGQwJiqJC/H6a415XaBnjq8uvxt5rb8Duq65D/6efwqSLXmaVSl4L8uaATbL31OAbCwmKDcxnA4ad8i6PtSgLGoLG6uwcijTmAhg64R0YufTlGxiAdZdYIo5llAUAfHhSNDU8vWhp3KVEg1IPvUIHAQI6Hd1JL3slYnybCqTMj5WVgp/4BuJOBNIu+Dl+/Lg82gIA5s6di+effx4HDx7Ehx9+iMsuuyxse4ZhcMstt2Dnzp345ptvsG3bNpSUlAx+27Tl80DWZ3bOdGSqMxJ6j1xtNvK14pDHo/21Yc9J2Z+xKH1JGgkpLQ4AbYFp7pGmhA8mR5MFk9IATuBwIpApCZqgxeb0zNntcAS8fUxnrADPC9AFxgVEQhL9xtPtFA+S03OLvQ1eLrI5XcaZa0HrdPB1dcK2+6u43t9vscBVJ/6O9RH8dWoH6uHjfchQmVCgzY+oMUuEMin4sQaDH0V2NticHIDn4aqvH/XPGAlptIUygcwPELxotzmGXshGY3YYrYzR+vy/0Lr95YhlDC/nw74e8Tu5pGDh0A1GSZXkoh5B96OdHih9HY2u+5GCQGmSOxDUwQw30ysSozE7NAdGWWim1kAzpWrEn9Vm78CxgTpQoEY0NYxGUPfTJQc//oGBpAT4PC+A1elk5/fByMa3Y3R+ihXJnNbCiGVgUvYiJBUf55MdnVcULRvVe83OEUsQhweNugjV/SRrnpTE4JleNq8dFq8NFKiYTpAURcnZn6G6n9iCH9tXX0Lw+6EqLYOqtGzMRL+xkqXOgFFpAC/waAkRCIdCqzXIPEf0Xup/47W4sj/2fV8DggBVRSUU2UMv+gd7xQvanJyZSU2dl8ljLsI/kzQ7bjxKX7K7c04u3H43LF7RHTdPE1vmRy57Dcr8AEEH43gyjkDiZYxDfUfh5jzIVGVgyhiMW6nKqAAAdDq7YfOG37VrZwREz7XHo+rOgjO9xLXxAi+XPOPJ/ADB4Kc1JPOjkia8D5P5CR1lEXPWJzDKYn7enDAn73gIDX4YnQ6MUbQL8I7SOw4QmxI8bi8KN50X+WcnefZfokiZHzMtdlcLPt+o9XDpBgl+Usg3PQfh8DuRqcoYdc1fKn0d7jsGXgid6VMDSqkExfPg+3uTdkEUeB6e1sFjLcSTW44mC2p2eAMyiarBouc4O76kCe7GEBdradJ1MkW/sUJRlDw7rMka/UKasfZs0FotvB3t8hiEWJC2NSwcmvURBAGHAsHvnJwZQ54fDdFFz2LQ7RzP4Cc3V+70Mij00Cpis7Uo0osXNbPHAuegsqh0kfe2tkDwxz58jaYp+OzxlzGkkteSggUjNgYkgl6hky/iDZbmsOdUZeWip5bLFVFzw7lc8HWJgY703e5x9cHH+6GgFXIZK1aK5dlqoWWvCgBiNo8LjHgYjGXHDvAuFxQFBSN2zQGA1WvDnsB+XVu6Mq41hhK14ytJomeXDyi+8HyUXHLxmM/+SxRdIPgZgAsIeMSdarofEvykkM9lofOSUZ8Aq0wV0LBq2H0ONFtb5McVajVm/uLnWPzow8jMMSHLpIJeRY+6ndLX1QnB6wWlVEIRMEuT9D6RhplGQ+r4arSeAMdzYucNRcHf2wu/1Trsaz1tbeKdI8PAcFowc8ZxPHY3HcKUzDI8fP6v8ej5vxm16DceZNFzFN0PADBaLTLPFkX5fTFmfzi7Hc7jYnATaUp4i70NZo8FSkaJmoyRSwTxEE30LA05dTc1gg94cI0FvMcDzmIGIAqeY5npNRgNq0GmKgNA+LBN8T1zQavVEPz+mPUdvMeDgQ/fB6tRx1XGcPiccoY2mV1eg4lW+qJoGpppAbF6hJZ3KSBis7LltvIOybtLlxf3uUpqfuhwdIHjxUwTo9WJVgkQNWODEfx+DLz/LgAg89z1MZm07mjdCb/AodJYNqpsWmjmB0j+jC+O41H36N+gr6rCkicfw/y/bcOiJx+F4pyVsDjG/vwUC1Lmx8P7QAeObf4U0/2Q4CdFdDq6UG9uAk3ROD3OjoRIMDQjt8kf7hWFjJIQ07J/P3ZfdR32XH0dvrr8anS/+cawQsxYcEt6n5JS+cTUahNPDrGInSUKdfnQshp4OS9a7e1gtFr5TsvdPHzpSxI66+bMBWsIHwfyTuOH+N3nj2D7vnfAuZhRi37joSIQ/DRH6fiSyDj7HNAaDbxtrbB/8/WI72vf/w3AcVAWl0CZP7T0cDDwe5+ROTXmVuRYiSZ6VuTkgs3MBDgO7saGpP7MUHy9YrBDazSgdbq42txDkbMQgzq+KJqWtWsjdSDxXi8G/v0umm7/CTr//jTM+w+gcGPkskykMsY33QfACRyK9YVxl5DiIZroGQC0Ab8f59Ghomf3oEnuANAm631G7uIcTJY6EypGCb/Ayb83YPgsr23vbvj7+8EYjDCOMISVoijwFI99PQcAAGeOIusDhHd8uf2epIueOZcLAzt24Ng9v0FX7QlsO/wy/vOtO3C452RaBD4AoGHVcpBLacXMKsn8EJKC1N4+O3sGMlSmpLznrGzxbk7y+4kqxPznC1GFmLEy2NwQCAoaSwyxnyBpipb1CXVmMdiRT4rDiCEFjpO9fUyDBrd2OrpQa24QR4XkL0ia6DdWyo0loCkaZo8FA25z1O0YrQ4ZZ50DAOh/49UR1yiXvCJkfQDgUEDvMztnZgKrHplIomeKouSur7EsfYW2uVMUFbfYWaJI7viKIHouLwdrNAJOW8TyMO/zYuD9f6Pppz9Bz/P/AGexgM3Jgd3qRMnFW1Hy7UvCyxjfviRiGWN3V6DkNYZZHyCYVW2xtcHtD7eOkPx+XPW14H3hwnx3wLVdPcpOLwmaokNEz6Fmh5GDH0EQMPDO2wCAjLPOBq2IPPyUYWiodQxMmWootAJ+s/52/HTlTVhUMDfuNYaiV+pgCJj8dTm7g5mfJJW9nAcPQPD7ocgvAJuXj7r+Jtg89rSY6C5BUZQsGRA0p+Zk9zSwU5p8hAqdz0hC1kdiVvZ0UKDQZu+A1WtFdkbesELM0ou3wuEdOmojFjySIDJwt+zjfOh0iheoeMpegGjHf7D3KBrMzTi7bDXUlZWw7vx82ODHcfgQOIsFjN4A3ZxwPcCONtE/Z07OTGSpM+NaSzJQMkoU6wvRYmtDk/XksF18mWefi4F/vwdPSwsc+/dBPz/yBZFzueA8ItoVRCp5mT0WnLS1gQIli9+TTVkEp2dA1P3Ydn0J1/FjkV6WFKROr0Tb3CWKA3f1gzM/DEOj7MLN0F57BXxWG5QmFTwuL1x+cf6S9dNP0PfWG+KUc4gloaxNm2E6fQUoloXF4Ufexk0oDZnf53F5h5Qx+t0DqDc3gQKFxfnzE9kVMZOpzkC2OhN97gE0WU5iRnZwiKiysAiMyQTOYoG7oV7OBAHBzJdk/ggk3uklUawvQqPlBNrsHVgC8RiP1vHlOnYUnpaToJRKZKxZG/H9GIaGzqjAq8fexdu1H8Phc0Kn0GL91DWYOaNm1OXtQl0+bGY72h1dKCoQg0BfdxcEjgPFxO/FFor9G/Hcr1+wEBRFweYTy0mSq3K6YFDoYfPawamVoEDKXoQk8E3PQTj9rqQInUPRK3WoDPjMNNlOjpmfhCAIcuZHcnbucHaBF3joWG3cmSyp46vB0gRe4IMdX82NUQMz2dtn2bKwGVluv0cOLFcVL49rHclEanmP5PQcCqPXI/OsswEAfa9Hz/44DuyX7xaVRUOHQUolrwpjKYzKke3/E6HMIA6jHSx61kq6n8aGIVmEZOELjLBR5ORCEIRg8KOJN/MjiW+75H0tlYf7P/0Uu6+6Dnuv/U+xPPzGGzCqKXT++ffofu4ZcGYz2Kws5H3vclT++jfIWLVGPvY4jofdw6Pf4oGdZ8W/PfyQC/CegKNzdUZlwtYW8SA3FAwyO6QoKlj6CvH74dxueDrEDK7U5u7lfPL+TrRMJ3kshWZ+VGXlAEWBs5jhGwg6Ufe/I96wmVasBKOPHBCMtYt7oT4oemazskEpFBD8frn8mii8zwv7AbE8p1+4CF7OCw8ndlEZ0ijzAwSNDn1qsYR+qmV+SPCTAj4LZCbOKDot6Z0eswJdX/u6Do2ZnwRnMYsdGjQNZbHYBdQm630K4+4oKzMUQ0kr4PA5RWOxklJxmrLdDn+Ekw3ncMCxTywdGE8PL3nt6foGbs6NXE02pmVVx/3ZkoUUhHa7esAw9LD7JPOcdaBUKnhONMNxcH/EbSRjQ8OixRHfa6xLXkB00bMivwCM0QjB74/ZoiBe5MxPXh5sPjvcnBsUqGHnx0UiX5sLhmLg5tzoD5Qko/v0vIC2l19FyQWbwWZmIu+7/4GKu3+DjNVnRh1KG21+n0Rol9d4EBwhM/T3Ein4cTSfEF3bTRmye3inswsCBOgU2oQD6+CYi6DXD61SyYG8J6Dv87S0wHn4EEBRyAjYQQyGoqgxd3EPFT1TNA1lgRi8jVb34zx6BILHDTYzE+qKStgk12uahZqJrUN2vJBEz161mOkiwQ8hYSiKwoB3AN3uXtAUjeVFkbUbo0Fqcf6m+yDcLjcKN2+MuF3hpvMS9pOQPECUBYWglWI9XrqjK45D7yPB0IzcHt5gaQKtUATFpxEupravdkHw+6EsKQ3TJQiCgB1tohvsyuLlY9JCHCs1WVW4ZcV/4ier/xO0hoMpUw21jokoMmcMBjm93//6a0N+J7zHA8dB6W5x6DHj5bw4PiCaDCa7xT2UaKLnUN3PWPn9hHr8SFmILHUmFHE6IzM0g/xAqazd0TGyT8+bbyNj4XxU3vtb0ZxyFM7xbfYOtDs6wVIMFuSOTpcSK5LoudnaMmSgq2R26G5qlMfJOBoCurtQc8PAnKsiXUHCAUVwzIUtzHdocOlr4L3AKItFi2Uzy8HQNDXmLu6S6HnIjK9RBj/2r8XGBt38haBoGjaf2OZvUOhTPtJiMLqA0aEnMNz0VDM6JMHPOBAqzMvKMOChTXfhf9fcjGxt8vUoRboCZKoy4ON9ONjThJKtW4YKMS+5GEWbzoN9ILK/xkhEcnZOpM09lCF+P8OYHUolL9OgrE+T9STa7B1Q0CyWFSY/sIwVhqFRlp+Hxv4TuOG123Hda7fiuldvxduNH0SdKp957npQSiXcTY3inW8I9oMHIHi9YHNywjpwJI7118HH+5GlzkxYkxEr0XQ/2jEccirwfIjmJw9dAW1ZvGJniaD4tjOmcQOc0wVWOfq7cinrMytnRszeRKMlT5sLg0IPP+8PE6oDon5KkZMLcJzsGm5vFL9vYY0MAUfs0XSmxTLmwtffD2tg3l3WMKaG4+HiLmV+BjxmuP1uKJLg9SPwPBz7xWNA8umSAsF0K3kBgCGQ+XEG4v1TbcQFCX7GGEmY93bjB7ju1Vtx4xu344bXbsfBrqNRL4SjgaIozAoIXr/q2AeLw4e8jZuw9KnHseSpJ7D0qcdhnDUTB396B9qf+ltCP2Ows7MgCLJ7azxt7qFMDQl+BEGI2gbraW8TAyKGgWFZuKZnR6uY9VmUPz/qiXE8kPQILx15O0yP8OLh6HoE1mRCxuozAQzV/tj2ihomw4JFEe8OJb3PnJwZY373GKnjC0DQN6ahLi6TwFjgrBYIPh9AUVBkZSUsdpYI7fgar3EDvMDLep+x7vIKhaKokBuLoTcSGrnlXSybOhoCNx8hQbbc6TXKwDqy2aF4k+Pv64Prm91gdTpoaqbJNz+RGA8X99ASX4ejOyleP676OnA2G2itTp6vJpW90jH4kYwOHQpxP5KyFyEuognzXkySMC8ScwK6n0O9R+H3c0OFmBwDV0cn7Hv3wLYnvtlSQDDzI5Wc+t1muPwuMBSDQt3IU5cjUWEsA0MxMHss6HMPBDM/J5rDLPitAUdn3Zy5YltyAJvXjm+6Rb1MKoXOo9EjZK7bAEqhgLuhHq6ADoP3+WAL6JsidXnxAo9DAWuDOdljp/eRKI3i9KwsLAKt10PweiOa1o0Gb0DszGZng2LZhAwOQykK6fiSxw1EKw8nadxAg7kJAx4zNKwas7PHphsvGtVRRM9AsOXdeewoeJ8PTimrW1Yhb5PoWIvBRBpzoa0ow/Sf3YaFf7ofxWeuxOJHH0bNzT8Y8abQ5xawqeacMXVxjzTjyzeKERf2rwNdXvPmy5oxu5T5SbNOLyCo+bEFJruTshchZsZDmBeJmswqKGgWAx6z3NIbKsRUl5Uj67xNAIDuZ/4Ov214J+VQOKdT9lyRyl6SiLFAl5fwdGolo5RHKDSYm6AsKBAdd71eeNvF9xd4Xvb2MS4PH1q4s2M3/AKHMkMJyo2lCa0hGYxGj8BmZMC0ag0AMfsDAOb9B8C7XGAyMqCOMNixxdYGq9cGFaNEdWb0u+VkkavJhoZVDxE9UzQN7dSx0f1Iep/BA03zE8z8SBfhLmcP/LwfLh8il4ej+PQkguTtMz93TtINKEdC8tFqNJ8IG30DANrpYiDmaTkJ5/FjEDgOjF4PNkuci+X0OWH2WAAEdTCJMjjzwzA0Mowa2OvqxS67627E7quuQ9/Hn4xowspxPB7a+RSmZJbhkfPvxaMX/DbpLu6hYy4kU1HObos6jmM4BEEItrgvDA6ytUqanzTM/MiT3RnxC0AyP4SYGQ9hXiSUjBLTMsVOp8O9kb1XsjduhrK4BJzdhu5nn4n5vaV5XmxWltyGKul9pJNbooR2plA0LQ8/lJyenUcOgTObQev10M+bL7+OF3i5gy6VWR9g9HqEzPXngWJZuGqPw1VXB1ttLVijEfoFiyJa/EuDTGdkTYtb/JsIouhZGnI6uPQVMDtMsu4n1OOHF3j0uPoAxD7QdDAZKhM0rBq8wKPL2QOO4yOWh/M2bkrKuAEf78fX3eIE96Xj1OUVSom+CGpGBTfnHjLWgzVlQFlUBAgC+gLGguryCvmGTNo+U5UBDase5TrCx1zIXXYvvDiky24kE9YT1hbs7tyH33/xGNp7+sE56aS7uIdmfmiVCmy2qFlKZMCpp+Uk/H19oJRKaGfOlh9PZ82PTimew6ThpiT4IcTMeAjzojE70PUjuT0PhmJZFFx1DUDTsO/5CrY9u2N630hiZ0nAmKjYWWJwen6w07P1c1HobFwa7u1zpO84+twD0LIaLMofeQDiWDJaPYIiMxO551+A6bffivx5M5B/1llY/OjDqPz2xRHvhA8Egp+5Y9jiPpjoZocBv5/62qjTwhNBdnfOyUW/ewCcwIGlWWSqE3NGpyhKLn1Jx26sPj2JcKTvGFx+FzJUJtnTajyhKRpTTBUAorW8i8eO5+RJaMvLoJsW9B6TzA2LkzCGI0udCTWjgl/g0OvuH77L7vU3odJEz4pL+r4FefOgY7Vj4uIud3w5Bnd8tUd9TTSkkpdu1hzQqqB4nhd4lJqKkK0ZfzPWkZBKcf3SZHePO+l6vlRCHJ7HkNAL4YuHh37JkyHMi4Y06qLJcgJ2n0NOYYaiLq9A1nkb0f/G6+h+9mlop02XBxlGI9JYi6DYeXSZnymmClCg0O3shcVjC+v44hwOef6VcdA4i08D7e3LChdDyUS2wh9PpKnyAIa4z14wfR0c1uhGgAxDo/LSi9D20nbU/fFBcA4HGJ0OhZs2ouSiLWGZiH73ANrsHaBAyb/v8SCa6FlVUgpaowHvcsHTclIOXkdLcJp7Hk5KYy00OaOyMijWF6LB0iyLeSXE8nByv49Sl9ei/Hkps1+oyqjEkf7jaDA34czS8O+PafEiFCxbhIx5c+GzWKDIzITX7YPLHzLTa5TfbUAMwor0BWi0nMCApx9+R1YMJqzskN+H3efA3u59AIBVJWOX6ZUyP2aPBS6/C8qCQjgPH0pI9Cydu6SSF8PQUKgp3LzyaljcVmRoTPB4fPC5hbSZ7yXdtDsVPEBRgCCAczjAmpIzjinVkOBnjIl2IdxQM/KFcDRkqTNRrC9Em70DR/qOY2nBwsjbbTwf9m++gbetFd3/eAaF190w7PvKwU8g8+Pyu9EbKEOMNvOjVWhQpC9Am70DDZYmzAkEP5zNCvfhA2C0WtAGY1jg1evqx+E+scyysnhZxPcdbziOh8Pqw4YpZ2HLjA2wex3QKNQ42HkUnb0D0DLRO9E0CqBt+8tofeHF4PsFSgGggLyNm2APJFUOBbq8Kk3l0CsjdyuNBYNFz5LOi6JpaKbWwHFgP1y1x5MY/ATnenU7xYArUbGzhCTeldq4xwqX3yVnX5fkR/4OjgehWVVBEOSMCsPQKFg0b2iwvXkjSrZugV8Qz09SIDBapDEXzZZWnFE5D4xOFzEAkrvsLJ4hz33ZsQc+3o8SfREqjWVDnk8WWoUGJqURFq8VHY5uZCXY7u7t6oS3rRVgGOjmzo86miP0mpAOAZCSUUJJK+DlfaA0GghO5ykV/JCy1xgTeiHcdsFvxkSYF43ZIV1f0aAVChRceTVA07B9tQu2QHo2EoLfD0+bePGRxlpId84ZKlNSLsDVIS3vqpxszPj5z7D4kYdQsHg+Fj/6MKbd8iOwbHC2zmdtX0KAgBlZNQm3Po8FHMfD7eBgGXBDcLH43SeP4HefP4L3mj6O+poRDfcGlQJCW9zHk2iiZyDY8u5pbRnR2ToWeI8HnFUU5Ctyc0MGmo7udy1NJx+c+Uk233Qfgp/3o0CXL2teUkG5oQQszcLmtaPbFXRNDw22Iw0/PqtcnD042qyuhFQ+azA3J9Rlxws8Pg3R9421tUOY6Flud4/vmJGMDbXTpoPR6aJ3AA9jhZEqpHZ3QSvqvU6lji8S/IwDoRfCsRDmRUMacHmkvxYcH12Doa6oRNb68wAA3c88Bc4e2czK29EOcBxorRZstnjnHTQ3TM7JUdJE2Pw2ZOiVsB07HugEuQG7r7oOAzt3yp0gPs6HnR2iVildsj6Dkbrszig6DQDwaduXcPldEbeNxXBPmsfm9ntQK7s6j5/eBxhe9GycOxfTb78VM394I3S0D1kmFfQqOmE/K0nsTGu1YHS6UXv8SBTpgyUNZ5SGhGQQOsE9lQ6+CkaB8sBstoaAkWgswfbMgmkwqY0Jd9YNJnTMRSJddsf669Dr6oOGVWPxOIjHgzO+Qtrde7rjmmEXHGS6KGUdwIki3dDyGlGndCoZHZLgZxwZae5PsqkwlkGn0MLld6FxhAGbWZsvgLKoCJzViu5/PBtxG3fIJPdgN4jU6TW6kpdEVcCOf33F8iidIP+SO0G+6TkIu8+BDJVJznKlK7Oyp6NQlw8358anrV9G3CYew71jA3XwCxxy1Fko0CbmrTQaIomeGYZG3rRK2OsbsPuq67Dn8qvFAaFvvjFi63I0QsdaAGJ7OgDkj7LspWE1yFRlAADaB2WvkoXZY0HdQAMAYMkYT3CPhepBLuqxBNtumxVTMsoTtrAYTOiYC7PLGneXnTS+ZlnBYqjGQd8nZ37sXWBMJtAaDSAI8qDdkfCbB+BuFI8B/YIFKesAThRJK+o/BYebkuDnFIamaMzMErM/h6J0fcnbKhTIv+IagKJg27VTFuiFMljvAyRP7CxhUhkwxVSGWYUzRiz/SKLHFUXLwNBMxG3TBZqicU7ZGgDAh62fwscNvXOMx3BPanGfkzMzJXeJUvDTYg0GP2LrcvQSynCty9GQp7nn5sLL+TDgMQNIvM09lEiTxpPJnq59ECBgiqkC2ZqsMfkZ8TA4+Ikl2FYbjNANo1GLl8FjLuLpsutzDcgl/PHK9IZ2fFEUFXfHl/0bMfOnnlIFNiMzpR3AiSAFPz6V+OUlZS/ChGFOjhT8RPb7CUUzZQoyAzN1uiKUvwa3ufMCL2smSgzJyfwAwMyc6XDbLMPekfocDlh8VtAUjdOLlibtZ48li/PnI1OVAZvXji87I2urYikF8AIvXwTGu+QlIZW92uzt8PP+uPVKseLrDYqdewJaFS2rScr4kqII4xaSyZ7OYMkrHag0lYMChT53P8wey4jBdsGm83Co46icIUsWJRH2eyxZ8c/aRX3ftMxq5CfoJB8vkmO9xWuF0+cKBj8xip5DS17A+IzmSCZS8ONRiaEC5yRlL8IEYUbWNNAUDYffAZvfOuLFJ/uCC6EsKARnsaD7+efkxwVBkDM/0liLbmcvfLwPSlqB3MDdXDLI1+RCbTANe0fKaLUwu61YkDsHJtXw7fnpAkMzOKtsFQDgg5OfDHHbBTDEcG/p00NLAc3WFth9DmhYtXw3P94MFj3Ho1eKh9A2964QsXMysl3FIWMukk2nowst9nbQFI2FeeMzwX0kNKxavkmRsj/DBdt5F27C04dfHbWz82CKIoy5GAkf78cX7eIonvE0MtWwGmSoxO6mDkdXXDO+OIcDzuPiTWeoq7PPLWDztLEdzZEsJMGzSyF+306lshdpdT/FMah1uHP1D1GVXQ6H1wWjSg23xxvVT4JWKJF/5dVoufdu2HZ+AcOiJdDPXwB/by94lwsUy8ongFBn52T6l5QZSnCo4ygKNm1A2/MvDnm+MHBHavPYsTLFjs7xcnrRUrzd9D56XH3Y13Mo4oWR43jYOcDDe5GRYYLZ7IDPF/xdSSWvmVnTUlbuk0TPtQP1OGlrRZmxBKxBl1Dr8nAEg59cdDtFbc5o29wlgpmfrrD272QgefvMzJo2rjYEI1GdUYkWWxvqzU1YnD8/LNguvXgrOKcTjFYLt8uDn+/4A9psnUkxOAwlUuZnJPZ1B/V9453tLNTlw+yxoMPRibyC2Du+HAf2AxwHZVGxPB4DEL/fz3z9GuYXz8Aj598Dl98DrUIDt8ebNm3uEtKx61SKARkpexEmBJKfxKHu47jhtdtxw+s/xXWv3oq3Gz8YdqK8pqoameeK3kRdf38KnMMBb0c7tOVl0NbUyO7KbUnW+0hkq7Pwct0HyL1wI0ou/daQO9KCrRfgqcOvoFCXn7LMR6KoGCVWl5wOAHjvxEfDprelpwZvIpW8Zo9zi/tgQkXPYzEgVOD5sNEWo53pNZh8bS4YioGbc6PfbU7KewJilnR3YIJ7KsZZDEd1oKFA6vgCgu7WVocXCpMJVocXDf2dOGlpg5JRIkudXPfh4kFjLmJBEjqvKDpt3AP+SANOvR0dIx7LkWZ5AYCH8+KTkzvxu88fwdGW5nHtAI4XqexlZ8V1kcwPYUIg+Um8dCSow5D8JABgw5SzwEU5lrMv2Ar7vn1gFQw0bityVyxFweypUGRkwOvxw+UHWm3J7fSSoCgKOkaHOz7+PX509lVY+q2L4Hc4weq08Lg8+N3Ox9Bm68QlNRemTUtoPKwuOQP/PvkJWmxtOD5Qj+lZU2N+bZ+rH+2OTtAUPa6uzpEYLHqWSiiAqPGRDfM2bkDxhefD6orvxO43m0U7fZqGIisb3SeS0+YuwdAM8rW5aHd0ot3RkbQRA03WE+hz90PFKFOmyYpGVeBmod3RKZvrSYQG21IHXKEuP+mu1NKYCzfnQZezZ8Rp8a22djRamlOm7wsVPSun5AE0DcHjht9shiI3crmf93rhOCTOc9MvXBz23KHeo/DyPuSos1CoK0i7gCcUfeD4sLKn3nBTkvk5RRmtnwStVKLkxpsw59e/gnnvXuy+8hpx6vKV18qtyxwlfiGSKXaWqM6YgjZbJx7d96+wTpCvO+twoPsIlIwyqmt1uqNX6nBG4CT+3omP4nqtZGw4xVSeFNHvaBgseo40IHTJ3x6FvmoKDv/y1/DGOQ1bzvpkZ4NimKDBoSY5ZS8gxOk5SWaHFEWhwdoEg0qP+blz0mLcSigGpV7OnDVamqNuJ5WkipOs9wGCYy6A2DrtpKzP/NzZMKmMSV/PSIRmfiiWhSJXFEH7htH9OA8fguD1gs3ODuuOBYCvuw8AABbmz0v7mzdJ82NhvAAAnvj8ENKdZPhJZFaVo/3NtyO3Lr+0HVunng0KwSGRyUQqZzVaT8DP+eVOEGmg4dKChaOeMp1K1pauAk3ROD5QjxPWlphfF9rinmoiOT0Pbl3u67Oj4fGnYD9yBD3/eG6EdwwnONA0D3afAw6/eCznJknzAwRLMKPt+GIYGmodA1OmGmfXnI6HNt2F786/MGFzx7FE+m7VRRhyKiF1cRYmWe8jETQ7HH6/u/wu7O4UbTfGU+gcitTxZfXa4PA5g6Lnjujt7tIgU8nYUMLt9+BwwHZkYV5qhzDHgqT5MTOiNQfJ/BDSntH6SYzYuvzGW5hdOAOVplKoWVXEbUZDgS4PWlYDL+dFi10sq5g9FuzvPQwgdSfCZJGtycSivPkAgH+f+Dim17j8bvmCNScNTB0pikKpXtL9hDs9S63LlEKJgqtE/yjrzs9lHUQshIudxZJXhsqUVHO7oiR0fEnaurcbP8B1r96K/3rzTtzw2u3Y0bJzWG1dqqiSdT/NUbeR9sdY3NgAsXss7er4Gl7ehwJdvuz+Pt6oWbXc7h+m+4mS+RH8ftj37wMA6BcuCnvuUN9R+Hg/8jQ5KR13Eis6Vrx+uJViAMc7nRD49C3TxUN6fSsJSWO0fhKxur9WZ46N4JimaFmfILXlftH+FXiBR5WpIuki61RwTvlqAMC+nkNySWc4jvbXghM45Glzxs3nZCTKjNKYi7ao22iqpwb9o55+Cn6bNab3Dg40Td5Mr8FIx1GXswd+PsI8hRiYSLOagGDm56StFR7OO+R5j9+DXlc/gOQ3M0iEjrmIhiAIcslrPOZ4DUdwzEVniOg5csDsqqsF73SAMRigqQ7X88klr7y5aV/yAkRdnJbVyMEPIAZApwIk+DmFkSbKXzzrvDA/iYtmbsDGmrOG9ZOI1f3VqBy7GnyoIy3Hc/isbReAiZ/1kSjWF2J29nQIEPD+yR0jbi+XvLJTX/KSiOT0HInsC7ZAWVwCzmZF99+fiqnrK9TjR8r8JKvTSyJDZYKGVYMXeNlHKB4m2qwmQBQcZ6oywAs8miKMvelwdEGAAL1CB4NSPyZrkDJKFq8NNm9kHUmduQFdzm6o0kDfF9bxNYLXjzQcWjdvASg6eIl1+d04HDCbXZif/iUvCb1CB4GmAPWpNd+LBD+nMJEmyj9ywb2ozCzD/374AHocfVFfO7L76wYc6jiKHHXyzA0HIwU/Pc4eNNiawFM8DAo95uXNGbOfOd6cU34mAGBXxx5YPNEzIrzAyyfO8Z7iPhyy6NnRMWzmhFYoUHD1tQDDwP71Xth27RzxvcPLXlLmJ3l6H0AMXqQLcSJjLibarCZA/MxVGRUAwlveJSTxd9EYZlfVrCpszEUkgvq+RSnX98kdX/Yu2bPHP9AP3u0O207geTj2iRqlwS3uB3uPwM/7ka/NHbNy4lggiZ6Dw01PDd0PCX5OcYZMlO9349XD/8ZJSxveaHxv2NdGdX+99BLkBtxfS5Lc5h5KhakUt664Ab/d8DNMLSzDQ5vuwu2rvg+1Ir06aEZDdUYlppjK4Rc4fNTyWdTtGi0n4PA5oWU1mGKqGL8FjoAseub9sug5GuqycmRvvgAA0P3cM/ANDETdlne7wQXKY4rc3KC7cxI7vSSCZofx634m2qwmCTmrGqHjSwp+xqLTKxRJ8xIp+AnV943XHK/hKArJ/DB6PRiDmPH2DDI7dDc3wz8wAEqlhnZGeIZ2opW8JCTRM6cWz7unitEhCX4mCZIAFQAurD4PAPBV59eyV08kIrUuL33qcRg3nI07Pn4AZpdVtn5PNgxDw5ihRn1/M2547Xb81xt34IbXbsfezv1pKSIdDecGsj+ftn0Jl98VcRvJ2HBmdupcnSMxnOg5ElkbNkJVUQne6UTXU09ELX9Jbe60VgdKo5HneiVb8wOEiG8d8Wd+eJ5HU/9JrJ+6OuLz6TarSUISDzdZTgzJ2AU7vfLHdA1FwwQ/n7ftCuj7KtNC35evFTV2Np8ddq8jaseXJOjXzZkLOuQmzeV34WjfcQATo8srFHm4qTzZnZS9CBOUCmMZFuXNgwABrzRE7uaSiDR1+dOT+wO294VjdgcTNGh8e0KISEfDrOzpKNDlw8258WnblxG3SacW98GUGoNOzyNBMQwKr74WlEIB56GDsOz4JOJ2stg5Lw9mjwU+3g+GYpCdZLdhACjSJZ75effER3h499+xYeqZuHjmeWk/q0miQJsHnUILH+9Dy6DfW5tNDEak/TJWRMv8cDyHz9sD+r6S9ND3qVkVstVZAMJFz55BA06juTof6DkCv8ChQJc/oqljuiEFP16VeNNFyl6ECc3mKevBUAyO9tfiaH/tiNuHTl2WZnqNhbkhMDFFpKOBpmicUyZmDj5q+Qw+zhf2fI+zF53ObtAUjZlZ01KxxGEpD+h+RhI9SygLi5Cz5WIAQM8L/4A3EOiEIut9coJt7jma7DHJehUFMhxmjwXOKNqdSHzdfQCvN76DNlsndjUdwIaqoLZu2wW/wYYpZ6XdrCYJiqLklvf6EN2P1WOH1SuaURaOcUehlNHpHDTmYn/vYVi8NhgUeszPnT2ma4iH8DEXYgATOt3d094OX2cnKJaFbk54die05DXRkAJ6ud09CcGPdOpO5Sk8LYKfvr4+3HLLLVi2bBkWLFiA6667Dg0NDfLzhw8fxve+9z0sWLAAa9aswX333QevN9iiyfM8/vSnP2HlypWYP38+rr32WrS0xG4cNxnJ1WbLXVOv1L8VccJ4NMZqppfERBSRjpbF+fORqcqA1WvDrs5wL5z9PWLWpzpjCrQKTSqWNyyhoudYZzVlnH0ONDXTIHg86HrisSHeId5xEDtLaFiN7OPSPoJuSeKEtQVPH/knAODM0hWYnzM3XFuXprOaQpF0Pw2WYPDTYhFvbLLVWVCPschYGnPhF7iwTrtPA0LnM4qWgqXTZwKTFPy0O7qgiJD5kbI+2hkzwWiC31OnzynfYE7E4EfK/DgDVTzOnnjZi2Fo6NU0jDolvBYLjDol9Co6JTKGtAh+brrpJpw4cQLbtm3Diy++CLVajSuuuAIulwsDAwO46qqrMGXKFLzyyiv41a9+he3bt+MPf/iD/Pq//OUveO655/CrX/0K//znP8HzPK655pqwAIkwlPUVZ0HNqNFqb8eewCDGkQjN/CR7ppfERBWRjgaWZrG2bCUA4P2Tn4QFowe6ReFnOnV5hRIqeo41eKBoGgVXXgNKpYarrhbm98PF95EMDscq+AGCup9YnJ4H3Gb89cCT8PF+zM6ejq3Vm+TnQjOk6Y4c/Jib5ePtpFnM3o1HaSbSmItORxdqzQ2gQGFFGgidQwlmfjpD2t07IXBiwB/q6hzK/t4j4AQORboC+T0mEpLg2THK4aYMQ8OkU6D79dfx1eVXY/d/XIWvLr9aHpc03gFQyoMfi8WC4uJi3HXXXZg7dy6qqqpw4403oru7G3V1ddi7dy/MZjNuueUWlJeXY+XKldi8eTM+/fRTAIDX68UTTzyBH/zgB1izZg2mT5+O3//+9+js7MR77w3fzTTZ0St1WBcQ277W8M6Qcksk+t1muPxuMBQzZmnx0Ro0TlROL1wKHatFj6sP+3oOAQAcXifqAmWJdPL3CSVc9Bx7xlWRm4vcS78NAOjd/iI87UHxqK9XLIUpc/PkrEC+JvliZ4nhxLehuP0ePHzgb7B6bSjSFeDKWf8v6YM/x4sSfRGUjBJOv0vu1DsZyPyMVyv24DEXOwKat7k5M5GpzhiXNcRK0OiwC2xWNiiWheD3wdPTA19fLzwnmgGKgm7+grDXfd29H8DEzPoAwcyPjRWDvESDH40CaH1pO1qf/9fQcUnbX4ZmnJN8Kf/Wmkwm3H///aipqQEA9Pf348knn0RBQQGqq6uRlSWKzP7xj3+A4zi0trbik08+wbx5Yk312LFjcDgcWL48KIwzGo2YOXMmdu/ePf4faIKxpnQFMlQmDHjM+KTtixG3l7I+Bbq8MU1JRzNoTGcR6WhRsyqsKjkdAPDvEx9BEATs6zwMXuBRoM1DrnbsPJVGSzyi51BMK1dDO3suBL8fnU88CsHvh8Dz8PeK2Z7xKHsBwbbu4cZc8AKPJ488hzZ7BwxKPf5z7pVjXhoaSxiawRRjOYCg349U9hovUW5xSNDp9nuwq0PMnqxME6FzKAXaPFCg4PA5YeecUAT8fpytbbB+LXr7aKqngjUGjV8dPieO9dcBmLjBj+TzY2XFm2PeGX/Za8RxSa+/CZVmfHWc6VNQBXDnnXfihRdegFKpxMMPPwytVouFCxfihhtuwB//+Ef8/ve/B8dxWLZsGX7+858DADoDPguFheH6k7y8PPm5RGHZobGhlJo7VVqtWVaF86vX4enDL+Dd5g+xsvS0YaeFdzjFO7RSQ1HE/ROJRPeZ2+HHeVVnYcuMDXD6XNAqNPB4vXA7/KCoyL+fic7ZFSvx/slPcNLWhkZrM5otrTCo9JibNzOtP2+lqRQA0Gpri3udxVdfjYY7boenuQnmd99C5qrV0BQXwWu1gsnOQJ9b9AMqMubH9N6JHG+lJjED0e7oAsNQEU/CLx5/Ewd7j4KlWdw0/0rkG9I3GI2VmqwpODZQhwZrM86mV8rBT5kp9u/3aCgL7HeLz4o6Wx0ULAujKgezcmvSLqPGsmrkaLLQ4+pDt6sb+qIieNta4Wprk0texsWLw/bboa4j4AUeJYYiFJsmVpeXRIbGACCY+eEdjriPjVjGJfkdTigUinGTM6RV8HP55Zfj0ksvxbPPPoubbroJzz33HMrLy9HY2Ijvfve7OP/889HS0oJ77rkHd955J37zm9/A5RJ9UZTKcOM7lUoFi8WS8FpomkJmZuTRDgBgNKaf8DRRzjOtxketn6HF0o6P2nfge/Mvirptl0csR9TkVwy7fyIxmn1mYsQvoELDAqfOrh9CJnTYOms9ykzFmJNfg7LcAlw06zw4vS5kauPb3+PJXLYGOCjewRtMarDxdGVl6kBdfy1aXvgXsmfWILMkD4af3QaFKQNuvxtFhnz0u8wozy+I684wnuPNYKoEQzNw+93gVB7k6sIDm/cbPsO/T4ht+f912uVYWJaeJch4WVA2E681vIsGSxM8rEssadMMphVXxPc7TJA5+mrcovxPzMmfDpvHjoem3IVeRz+yTYYx/9mJUJ5ZjB5XH8z8AIoqy2Dd/RWsR47BcVz08Ck5cyXUIefF/QfE8vWKisVxny/ThQxBC4ai4VaKAQ/vdCb0WXi/EoxOFzEAYnQ6sHodTOz4hSRpFfxUV1cDAO6++27s378fzzzzDJRKJSwWC/70pz8BAGbNmgWTyYQrrrgCV1xxBdRqMe3s9XrlfwOAx+OBRpP4VZLnBVitQ7uNGIaG0aiB1epK606OeLlwygb8+ZvH8XbtR1iWtxQ5mqyI2zX2iZqObCYHAwOx1X5P1X02FtA0hY1Tz8Krx97FX3Y9DYfPCZ1Ciw01a3DB9HVwO/xpKfRWClpoWDVcfjeOtDTIZbBYUcxbiDmLFqD91ddR94c/g3M4wOh0KNx0Hu668GY8tOc5mM2xtaEnerwVaPPQZu/AkbZGzM0NnkuO9dXhsa//AQDYXHUuZhhmxHzspzs5dB4YisGAy4LPGvYAEEvaNot7hFeOHpqmoNaxaOw/MfRY16XnsZ6jEkuvDT0nMSOzCKzRCHdnJ1i9HmxGBlxKHVyBY8PudeBglziSZqZxYh8zOoUObpVY9vLb7ejvs4XNLYsFjYJC4eaNaP3nC0OeK9y8EV63Fy6fZ9RrNRo1MWV9Ux789Pf3Y+fOnVi3bh3YQNRH0zSqq6vR3d2Nrq4urFmzJuw1kt6nubkZxcXiSba7uxtlZWXyNt3d3Zg2bXSeKH5/9BMnx/HDPj/RmJZRg5rMatQO1OOV2ndwxaxvD9nG5Xej1yXOAyvQFsT9+U+1fTYWqHUMXjv+Hl468rb8mGTuCAAbppwFryM992Gpvhi15gY0mk+iUBufDYJeTaP9tTfQ+sKL8mOcw4HW5/8FAQIuOvPsMT/eCnX5aLN3oMXSjpmZ0wEAXY5u/HX/0+AFHovz52Nd2Vmn1DFMg0G5sQSNlhP46MTnAET903h8RrWOkY1MJdL9WM/XiE0eXt6H3MULULp2JXwWCxQmExztHfALkAPuvR0HwAs8SvVFyFZlT+jjRq/QoUsZmD0oCPDaHWDizEQ7BRrFF54P8Dw63nw7eIOzeSNKtm6BxTG+nlgpL6r29vbiRz/6EXbuDA469Pl8OHLkCKqqqpCfn4/jgZSihPT/yspKTJ8+HXq9Hrt27ZKft1qtOHLkCJYsWTI+H+IUgKIobKkSx17s7vp6iOsrEOzIyFCZ5A4AQvKY6OaOiYqeRxJDdr7xNsqzy8b8cxfrCmFQ6eERPKAoCnafAw8f+BtcfhcqjeW4bPq30nbfjwbJ7NDJuVBqKkJlRtkIrxg9E/VYL9QVoNhQgOsXXYre99/H7quuw97rbsTuq67DwJe7wlq2g8aGE2ucRSR0Ci04hoKgEBMUiXR8cRyPukf/Bn1VFZb87TEsfVocl5S3cdO4Bz5AGmR+ampqsGrVKtx111246667YDKZ8Mgjj8BqteKKK65AQ0MDrr32WvzhD3/A1q1b0dbWhv/7v/+T29oB4LLLLsN9992HrKwsFBcX43e/+x0KCgpw7rnnpvjTTSzKjCVYnD8fe7r24ZX6t/D9BdeGPS8FPyVpMGvnVCR2c0caHJde5QAAKIvT6VkiFjGkz+EATSvH7HMzDI21Nctx0YJ1sHnsMKnV6Oxpg5JVIFudievnXg4FoxiTn51q5ubNwPyy6ZiTPx1Wtw0ZGhM8Hh98bmHMLkgT9Vgv0Obi8lkXoOeVN9D2/NAsJSgKeRs3ocNlx/GBegDAwvyJ2eUVij5ksjvj84suz3E6T/j6+9H/4Yfo/+ADVP/2d8ifNgVmswM+X2oyYikPfgDggQcewP3334+bb74ZNpsNixcvxrPPPouioiIUFRXhkUcewUMPPYSnnnoKmZmZOOecc/DDH/5Qfv0PfvAD+P1+3HHHHXC73ViyZAkef/xxKBSn5slqLNk8ZT32dR/EsYE6HO2rxYzsGvm5tjE2N5zs8LwAQ8DcMdJFQTJ3tPBjr8dIhLJBTs+xjqLgeQGsQTesGFKp18NhGb0eIBIMQ0NnVOD9o1/i7bqPZe3J+qmr8X9rf4T23j4YlPox+dmphmFozC+bjleOvRNRYzZW4zkm6rGuZJWYlTUDe994IOLzHa+/idKLt+LIieMQIKDMUIIczcTvCtQHjn+/WgHGmljmx/r5p4AgQFMzDco80TMplVZtaRH8GAwG/OIXv8AvfvGLiM+vXr0aq1dHnpoMAAzD4JZbbsEtt9wyRiucPORosrCq5HR82PIpXm54E9OyquWW09bAwMOxmuk12Qk1d5R0D6Gku7mj5PTs8rvR7uhCaYzHiSAI8Li9UcWQBZs2wO10j9mJUhqi++KR4D53+Jx46cjboEBhQ9VZcDtiG9sx0VCoKbx6fHjdDTcGOt2JeqzTNAWv3TZiy3aT7QSAievtMxh9wP7Eq2ahQvyT3QWeh+XTHQAA06ro1/LxJOWaH0L6sa5iLTSsGm32Duzu/AaAOGm53TG2M70IE9vcMdTpucXWGtdrXT6gZOsWlHz7EjA6McXO6HQovvRi5F24CR5ubE5VI2pP6tJTe5IMUq27mYjHOs8LUOmN8jE6GEanA6PTYn9gJM2pEvxIRoceqd09zsyP88gh+Pv7QGt10C9anPT1JUJaZH4I6YVeocO68rV4peEtvN74LhbkzUW/ux8+3g8lo0TuKZDGTVc4jofD6sOGKaK5o8vngkahgdvjTdsJ4aGUGsWOrxO2VpyOpTG/juN4WBw+5G3chNKLt8LvcILRabC/7TBe/vp5XDbt0jFZ70TVniSDVH/2wce6ZGSazse6IAjos/ajYNOGMM2PROHmjeg2d8PqsaHcWIrsKJYhE43gcFMxEI637GXZIXpkGZefDlqhHGHr8YFkfggRWV1yBjJVGeLYi9bP0e3qRampCDWZlWnnvHqqwXE83A4ODpsHRrUBDpsn7SeESyQqegbEz2338Oi3eGDnWTx/4F3cu2sbKH7szPYm4xBdiXT47NKxbhlwg3PSsAy40/5Y73e7kXvhRhRfenFYlrLk25egZOsWPH/8HQCnTtYHCAl+FPEPN/VbLLDv3wcgfUpeAMn8EKKgZBTYPGUdPmj9BNOKKjA7bxrmlFbDpDbC6/WPaScIQUSSO6SZ7GFYygxi2cvqs4GiBUCg49ZtiJPRBTmAGsuZXhNVe5IM0umzS7/ziYBJYcKdn/wB3zvjfCz51sXgnU4wWi08Li9aBwaws00cdXFKBT+Bye52ecRF7Jof6xefARwH9ZQqqIpLxmR9iUCCH0JUlhUvwuppi/FW7Yd48Msnx60ThDBxydfn4taVN2JWXg1cPjf0SjXcHm9CwXK3Sxxumq8du2nuQFB7Aog6l0jH+anKZP7siaKgWfj8ftzz5SP4nyU34LQpc+WW7a86voEAAZXGcmSpM1O91KShl4ebxjfZPR2FzhIk+CFERaVh8FbtB+PeCUKYmEgt4/VHm0YdLAuCEDLNfWyDn4moPUkWE11jlioKdfnocvbgpLUNp2GunJ39uitgbHgKePuEIpVGnUrxg8Ya/LiOH4Ovuwu0Wg3DktPGbH2JQMQbhIhInSDv1H0c8fl0dWAlpA6pZfylI2/LIlopWH712LtQqGM/VqxeGzycFxSoqHPmkslE1J4ki4msMUsVhTrRp6bd3ik/ZvZY0GhpBgAsyJ2TimWNGUpGCSWtCA43jTH4sXwqCp0Npy0DrVKN2foSgQQ/hIjE3glCgh9C8tumpaxPtiYLLD1+CWpRe8KfkhqfkZiIGrNUEQx+uuTHvuk+CAECppgqkKnOSNHKxg6dQie3usfi88PZbLB/LeqfTCvXjOXSEoIEP4SIpEMnCGHikOxguUsueY2d2JlASJRCXQEAoMPRJQfKX3fvB3BqCZ1DMSh1cKuCre4j3SBYd34Bwe+Hqqwc6oqKcVhhfJDghxCR0E6QSJzKXTCE+IklWNawKnh83pjer9sZEDtrxlbvQyAkQp42BzRFw+13o881gH63GY2WE6BAYUHeqVXyktApdHLZCxwHwRN93IwgCHLJy7QyvYTOEiT4IURlIjqwElLDSMHy+qmrsb/zCH715X043Hd8xPfrdo2P2JlASASWZpGnEbOSrZYOWehclVGBDJUplUsbM/QKHfwMIDCi79Zwomd3fT28He2glEoYTls2XkuMC9LtRYjKZO6CIcTPcG3Tm6edg3s+eQi97n78Zf/jWJA3FxdP3Rz1QiFlfkjZi5CuFOry0ensRoulA3s6pZLXvBSvauzQK3QARcGvUUBh58A57FBkR3b7t3z6MQDAsHgpGG3kbHCqIcEPYVg4jgfnADxON2iahoV3k1IXISLDBcsuG4drZ/0H3mz6Nz5u/RzfdB/A0b7j2DRlHVYVLw+bAM8LPNRKFQycfsw9fgiERCnU5aPe2oR2Wwd63X2gQGH+KdblFYpkdOhTsVDYo3d8cU4HbHt2AwBMq9eM1/LihgQ/hJiYSA6shNQxXLCsZtW4aOpmLC1YhH8e345m60m8WPcadnXuxXembcWUzHIo1BTUKjVuOeN6GNUGeL1++N0gWUZCWsEwNM6dthLfXrQJVrcNly+4BPW9zchSmk7ZY1UabupVMdAietnLtutLCF4vlEXFUE+pGscVxgcJfggEQtIZLlguNRThfxbdiM/bv8KrDW+jxdaG546/iF+d/WO8efwDvF0X2Wn4VL2oECYWkpnnv4/uwjshx+r6qWswdUblKXusSi7P7mGGmwqCIA8xNa1andY+cCT4IRAI4w5N0VhZvAzzcmfh5fo3sbp6Kd44/j5xEyekPUEzz+A8NIfPiZeOvAWKOnWPVb3s8iz+P9J8L8+JZnhaToJiWRiXnT6ey4sb0u1FIBBShlFpwBWzvoN5BTPxTt0nEbchbuKEdCHZZp4TCansZWejT3a37PgYAKBftBiMXj9ua0sEEvwQCISUQtMUnF4XcRMnpD2T2fneoBSDGbsicvDDu92w7toFYGRvHyk2TGWMSIIfAoGQUoibOGGiMJmPVS2rARDU/Azu9rJ9tQuCxw1Ffj4006ZHfA+GoaHWMdAZVLC4bdAZVFDrGDDM+IciRPNDIBBSSqhBoqTxCYW4iRPShcl8rDI0Ay2rgVvpBjB0vpfs6LwistBZEoq/euzdIT5gqWhqIMEPgUBIOcMZJEonRgIhHZjMx6peoYNbZQEQXvbytLTA3dQIMAyMp58R8bWSUDw0aExlUwMJfggEQsohbuKEicLgY9Xlc0EzSY5VnUIHu1T2cgYjFcnRWT9/AVjTUNf2WITiW2ZsgMc5fia6JPghEAhpAXETJ0wUpGOV83qQkWGA2eyAz3fqBj0SeqUOvYHhplLmh/d6Yf1yJ4DoQufYheL0uJnpEsEzgUBIK0SDRJ4EPoS0RzpEJ8uhqlfo4FGJmR/B6wXv9cK+dzd4pxNsdja0M2dFfF06CsVJ8EMgEAgEAmFE9AodvCwFgQqWvmRH55WrQdGRQwpJKL5+6pqIz6dCKE7KXgQCgUAgEEZEp9CKk93VCihcXrjq6+GqqwUoCsYzVg77WqvdiQ01ZwIQ8E7dJykXipPgh0AgEAgEwojoA0aHXhUDhQvof0fs1NLNnQdFZuawr32r4QMcGTiGKxZcgq0zz0u5UJwEPwQCgUAgEEZEmu/lVtEwGY1gBA6s0Tiio3O/ewAftX4GP+9Hv9kGhyb1QnES/BAIBAKBQBgRvUKHYkMBFt+0CfnTZsFnsUBhMsHr9cPlp6Jmb95ofA9+3o+pGVMwK3t6WgjFSfBDIBAIBAJhRDI1Gbhrzc3offlN7P7NH8E5HGB0OhRu3oiSrVtgcQwtX7XY2vFV59cAgC3VG9Nm6CsJfggEAoFAIIxIkd6EnlfeQNsLL8qPcQ4HWv/5AgAgb+Mm2Lnw17za8BYECFiUNw/lxtLxXO6wkFZ3AoFAIBAIw0JRFDRaNTrfeDvi8x2vvwmVRhmW2TnaV4uj/bVgKAbnV60fr6XGBAl+CAQCgUAgDAtNU/A7HGEzvULhHA74HU7QdMADSODxcsObAIBVJcuRo8ket7XGAgl+CAQCgUAgDAvPC2B1OjA6XcTnGZ0OrE4ruzTv7vwGbfYOaFg11lecNZ5LjQkS/BAIBAKBQBgWQRDgcXtRsOm8iM8Xbt4Ij0t0afZxPrze+C4A4NzyM6FXRA6YUgkRPBMIBAKBQBgRlw/I37IZgIDON96O2O0FAB+3fo4BjxkZKhPWlKxI7aKjkPLgp6+vD/feey8+/fRTeDweLFmyBLfeeiuqqqoAAN3d3bj33nuxY8cOMAyDFStW4Gc/+xmysrLk93j22WfxxBNPoKenB7Nnz8Ydd9yBmTNnpuojEQgEAoFwysFxPF468iFmnTEDiy++CLzTBVanhcflldvcHT4n3j3xEQBg85R1UDKKFK86Mikve9100004ceIEtm3bhhdffBFqtRpXXHEFXC4XvF4vrrrqKrS3t+Ppp5/Gtm3bcOzYMdx6663y619++WX89re/xQ9/+ENs374dJSUluPLKK9Hf35/CT0UgEAgEwqmHz+/DPV8+gie/fhl2nkW/xQO7h5f9fd5t/hAuvwvF+kIsLViY4tVGJ6XBj8ViQXFxMe666y7MnTsXVVVVuPHGG9Hd3Y26ujq88cYbaGtrw4MPPoiZM2di3rx5uO2229DU1AS73Q4A+Otf/4rLLrsM559/Pqqrq/HrX/8aGo0G//rXv1L50QgEAoFAOOXQBfQ7va5+cBwfNom9z9WPT1o/BwBcWHUeaCrl+ZWopHRlJpMJ999/P2pqagAA/f39ePLJJ1FQUIDq6mp89tlnWLZsGXJycuTXrFy5Eu+//z70ej36+vrQ3NyM5cuXy8+zLIvFixdj9+7d4/55CAQCgUA4lZHEy3afc8hzrze+C7/AYXrmVMzIqhnvpcVFyjU/EnfeeSdeeOEFKJVKPPzww9BqtWhqasLixYvx0EMP4ZVXXoHf78eKFStwyy23wGg0orOzEwBQWFgY9l55eXk4duzYqNfEskNjQ4ahw/4mjAzZZ4lB9ltikP2WGGS/xc9k3GcmjQEA4PA5wq6RJ62t2N31DQDgomkboVAwUd8jHfZb2gQ/l19+OS699FI8++yzuOmmm/Dcc8/BbrfjlVdewfLly3H//ffDYrHgnnvuwY033oi///3vcLlcAAClUhn2XiqVCh6PZ1TroWkKmZnR2/OMRs2o3n8yQvZZYpD9lhhkvyUG2W/xM5n2WRHESozT75SvkYIg4M/7ROfnFeVLMa98Wkzvlcr9ljbBT3V1NQDg7rvvxv79+/HMM8+AZVlotVrcf//9UChExbjJZMK3vvUtHDx4EGq1GgDg9XrD3svj8UCjGd1O5XkBVuvQtB7D0DAaNbBaXVEn2BLCIfssMch+Swyy3xKD7Lf4mYz7jHeL2Rqrx47+fjsoisKh3mM41H0cLMVgQ9nZGBiI7AItMZb7zWjUxJRRSmnw09/fj507d2LdunVgWXEpNE2juroa3d3dKCgogCAIcuADAFOnTgUAtLa24rTTTgMgtsNLrfHS//Pz80e9Pr8/+i+F4/hhnycMheyzxCD7LTHIfksMst/iZzLtMzUlJh04gYPd44KKUeKl428AAFaXnIEMRUbM+yKV+y2lhcre3l786Ec/ws6dO+XHfD4fjhw5gqqqKixZsgTHjh2D2+2Wn6+trQUAlJeXIzs7G5WVldi1a5f8vN/vx549e7BkyZLx+yAEAoFAIEwClIwSSlpMSDh8Duzq/Brtjk5oWA3WVaxN8epiJ6XBT01NDVatWoW77roLu3fvRm1tLW677TZYrVZcccUV+Pa3vw2GYfA///M/qKurw969e3HHHXfgtNNOw6xZswAAV111Ff72t7/h5ZdfRn19PW6//Xa43W5cfPHFqfxoBAKBQCCckuiVehhUerh5Nz5u/QwAsL5iLXQKbYpXFjuUENqknwJsNhvuv/9+vP/++7DZbFi8eDFuu+02ubzV3NyMe+65B7t27YJSqcTZZ5+N2267DUajUX6Pxx9/HE8//TTMZrPs8DxjxoxRrYvjePT3D61bsiyNzEwdBgYckybNOVrIPksMst8Sg+y3xCD7LX4m4z5jGBpt3hZMzamEzeOAQaXD0e46FCtKQCF6h1coY7nfsrJ0MWl+Uh78pCsk+EkeZJ8lBtlviUH2W2KQ/RY/k22fMQwNnVGBV46+g3fqPoHD54ROocX6qWtw4Yx1cFh9MQmY0yH4SZtuLwKBQCAQCOmLQk3h1WPv4qUjb8uPOXxOvHTkLVAUsGHKWeCGb/RKGyaPMxOBQCAQCISEoCgKapUSb9d+HPH5t2s/hlqlBEVR47uwBCHBD4FAIBAIhGGhaQoOrxOOCGMtADED5PS5QNMk+CEQCAQCgXAKwPMCdEpt1I4unUILrUIDnp8YMmIS/BAIBAKBQBgWQRDg9nixoWZNxOc31KyB2+PFROmhIoJnAoFAIBAII+JzC7hg+joAosZH6vbaULMGF0wXu70mCiT4IRAIBAKBMCIcx8Nh9WHDlLOwZcYGOH0uaBUauD3emNvc0wUS/BAIBAKBQIgJjuPBOQCP0w2apmHh3ROm1BUKCX4IBAKBQCDEhSAI4LiJF/RIEMEzgUAgEAiESQUJfggEAoFAIEwqSPBDIBAIBAJhUkGCHwKBQCAQCJMKEvwQCAQCgUCYVJDgh0AgEAgEwqSCBD8EAoFAIBAmFST4IRAIBAKBMKkgwQ+BQCAQCIRJBSVMRF/qcUAQBPB85F3DMPSEmmGSDpB9lhhkvyUG2W+JQfZb/JB9lhhjtd9omgJFUSNuR4IfAoFAIBAIkwpS9iIQCAQCgTCpIMEPgUAgEAiESQUJfggEAoFAIEwqSPBDIBAIBAJhUkGCHwKBQCAQCJMKEvwQCAQCgUCYVJDgh0AgEAgEwqSCBD8EAoFAIBAmFST4IRAIBAKBMKkgwQ+BQCAQCIRJBQl+CAQCgUAgTCpI8EMgEAgEAmFSQYIfAoFAIBAIkwoS/MQIz/P405/+hJUrV2L+/Pm49tpr0dLSkuplpT1dXV2YNm3akD/bt29P9dLSkkceeQTf+973wh47evQoLrvsMsyfPx9r167F008/naLVpS+R9tsdd9wx5Lhbu3ZtilaYPpjNZvz85z/HqlWrsHDhQnznO9/Bnj175Od37tyJrVu3Yt68eVi/fj3efPPNFK42PRhpn1155ZVDjrXBx+NkpK+vD7fccguWLVuGBQsW4LrrrkNDQ4P8fErPbQIhJv785z8Lp512mvDRRx8JR48eFa666irh3HPPFTweT6qXltZ8/PHHwpw5c4Suri6hu7tb/uNyuVK9tLTjmWeeEaZPny5cdtll8mP9/f3CaaedJvz0pz8V6uvrhRdffFGYM2eO8OKLL6ZwpelFpP0mCIJw8cUXCw888EDYcdfX15eiVaYPV155pbBp0yZh9+7dQmNjo/B///d/wty5c4WGhgahvr5emDNnjvDAAw8I9fX1wmOPPSbMnDlT+OKLL1K97JQy3D4TBEFYvny58Nxzz4UdawMDA6lddBpw6aWXCt/61reE/fv3C/X19cL3v/99YcWKFYLT+3IJJQAACXhJREFU6Uz5uY0EPzHg8XiEBQsWCM8++6z8mMViEebOnSu8/vrrKVxZ+rNt2zZh8+bNqV5GWtPZ2Slcf/31wvz584X169eHXcT/+te/CitWrBB8Pp/82P333y+ce+65qVhqWjHcfuN5Xpg/f77w3nvvpXCF6Udzc7NQU1Mj7NmzR36M53nh7LPPFv7whz8Id955p3DxxReHveZHP/qRcNVVV433UtOGkfZZb2+vUFNTIxw+fDiFq0w/zGaz8KMf/Ug4fvy4/NjRo0eFmpoaYf/+/Sk/t5GyVwwcO3YMDocDy5cvlx8zGo2YOXMmdu/encKVpT/Hjx9HVVVVqpeR1hw+fBgKhQKvvfYa5s2bF/bcnj17sHTpUrAsKz+2bNkyNDc3o7e3d7yXmlYMt99OnjwJp9OJKVOmpGh16UlmZia2bduGOXPmyI9RFAWKomC1WrFnz56w8xwgHm979+6FIAjjvdy0YKR9dvz4cVAUhcrKyhSuMv0wmUy4//77UVNTAwDo7+/Hk08+iYKCAlRXV6f83EaCnxjo7OwEABQWFoY9npeXJz9HiExtbS36+/vx3e9+F6effjq+853vYMeOHaleVlqxdu1a/PnPf0ZpaemQ5zo7O1FQUBD2WF5eHgCgo6NjXNaXrgy332prawEAf//737F27VqcffbZ+OUvfwmbzTbey0wrjEYjVq9eDaVSKT/27rvv4sSJE1i5cmXU483lcmFgYGC8l5sWjLTPamtrYTAY8Mtf/hKrVq3C+vXr8Yc//AFerzeFq04v7rzzTixfvhxvvvkm7r77bmi12pSf20jwEwMulwsAwg5+AFCpVPB4PKlY0oTA7/ejsbERFosF3//+97Ft2zbMnz8f1113HXbu3Jnq5U0I3G53xOMOADn2hqG2thY0TSMvLw9//etfcdttt+Gzzz7DjTfeCJ7nU728tOHrr7/GT3/6U5x77rlYs2ZNxONN+j+5mIsM3me1tbXweDyYO3cuHnvsMdxwww3417/+hTvuuCPVS00bLr/8crz00kvYtGkTbrrpJhw+fDjl5zZ25E0IarUagPjll/4NiL8gjUaTqmWlPSzLYteuXWAYRt5vs2fPRl1dHR5//PEh6XXCUNRq9ZCLjnRi0Gq1qVjShOCGG27A//t//w+ZmZkAgJqaGuTm5uKSSy7BwYMHh5TJJiPvv/8+fvzjH2PhwoW47777AIgXn8HHm/R/cq6LvM9++ctf4tZbb4XJZAIgHmsKhQI333wzfvKTnyAnJyeVS04LqqurAQB333039u/fj2eeeSbl5zaS+YkBqdzV3d0d9nh3dzfy8/NTsaQJg06nCwsYAWDq1Kno6upK0YomFgUFBRGPOwDk2BsGmqblwEdi6tSpAEBK1QCeeeYZfP/738eZZ56Jv/71r/Idd2FhYcTjTavVwmAwpGKpaUO0fcayrBz4SJBjTdT4vPnmm/D7/fJjNE2juroa3d3dKT+3keAnBqZPnw69Xo9du3bJj1mtVhw5cgRLlixJ4crSm7q6OixcuDBsvwHAoUOH5DsBwvAsWbIEe/fuBcdx8mNffvklKisrkZ2dncKVpTc/+clPcMUVV4Q9dvDgQQCY9Mfec889h1/96lf47ne/iwceeCCs9LB48WJ89dVXYdt/+eWXWLhwIWh68l4uhttn3/ve9/DTn/40bPuDBw9CoVCgoqJinFeaPvT29uJHP/pRmMTB5/PhyJEjqKqqSvm5bfIezXGgVCpx2WWX4b777sMHH3yAY8eO4eabb0ZBQQHOPffcVC8vbamqqsKUKVPwy1/+Env27EFDQwPuuece7Nu3DzfccEOqlzchuOiii2C32/Gzn/0M9fX12L59O5588klcf/31qV5aWrNu3Trs3LkTDz74IE6ePIlPPvkEt99+OzZt2jSpuw+bmprw61//Gueccw6uv/569Pb2oqenBz09PbDZbPje976HAwcO4L777kNDQwOeeOIJvPPOO7jmmmtSvfSUMdI+W7duHV599VX84x//QEtLC9566y389re/xdVXXw29Xp/q5aeMmpoarFq1CnfddRd2796N2tpa3HbbbbBarbjiiitSfm6jhMnavxgnHMfhgQcewPbt2+F2u7FkyRL8/Oc/R0lJSaqXltb09vbi/vvvx6effgqr1YqZM2fixz/+MRYvXpzqpaUlt912G9ra2vD3v/9dfuzAgQO4++67ceTIEeTm5uKqq67CZZddlsJVph+R9tvbb7+Nbdu2obGxEQaDAZs3b8Z///d/y+WKychf//pX/P73v4/43JYtW3Dvvfdix44d+N3vfofm5maUlJTg+9//Ps4777xxXmn6EMs+e/bZZ/Hss8+ipaVF1pZdd911kzpbBgA2mw33338/3n//fdhsNixevBi33XabXBZM5bmNBD8EAoFAIBAmFZM7LCUQCAQCgTDpIMEPgUAgEAiESQUJfggEAoFAIEwqSPBDIBAIBAJhUkGCHwKBQCAQCJMKEvwQCAQCgUCYVJDgh0AgEAgEwqSCBD8EAoFAIBAmFST4IRAIpyxr167FbbfdFvX52267DWvXrh3HFREIhHSATfUCCAQCYax48MEHJ/V8JQKBEBkS/BAIhFOWmTNnpnoJBAIhDSHBD4FAOGVZu3Ytli5dinvvvRcWiwX33nsvPvjgAwiCgEsuuQQ8z6d6iQQCIQWQ4IdAIJzy8DyPa665Bm1tbbj11luRkZGBxx57DAcPHkReXl6ql0cgEMYZEvwQCIRTnh07duDAgQN49NFHsWrVKgDA8uXLidiZQJikkG4vAoFwyrNnzx4oFAqsXLlSfkyr1WL16tUpXBWBQEgVJPghEAinPBaLBRkZGaAoKuzx3NzcFK2IQCCkEhL8EAiEU57MzEwMDAyA47iwx81mc2oWRCAQUgoJfggEwinP8uXL4ff78f7778uPeb1efP755ylcFYFASBVE8EwgEE55li9fjhUrVuCOO+5AX18fiouL8fTTT6O/vx/Z2dmpXh6BQBhnSOaHQCBMCh588EGcf/75+NOf/oT//u//RkFBAS655JJUL4tAIKQAShAEIdWLIBAIBAKBQBgvSOaHQCAQCATCpIIEPwQCgUAgECYVJPghEAgEAoEwqSDBD4FAIBAIhEkFCX4IBAKBQCBMKkjwQyAQCAQCYVJBgh8CgUAgEAiTChL8EAgEAoFAmFSQ4IdAIBAIBMKkggQ/BAKBQCAQJhUk+CEQCAQCgTCp+P8MI3IoYUSBSwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lineplot(data=df_result, x='id', y='travel_time', hue='type', marker='o')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "metadata": {},
   "outputs": [],
   "source": [
    "from datetime import datetime\n",
    "from datetime import date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "metadata": {},
   "outputs": [],
   "source": [
    "today = date.today()\n",
    "now = datetime.now()\n",
    "today_str = today.strftime(\"%Y-%m-%d\")\n",
    "current_time = now.strftime(\"%H-%M-%S-%f\")\n",
    "current_time\n",
    "df_result.to_csv(f'./result/vrp_result_{map_size[0]}x{map_size[1]}_{num_trial}_{today_str}_{current_time}.csv', index=False)"
   ]
  }
 ],
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