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golomb_sat.cc
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golomb_sat.cc
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// Copyright 2010-2021 Google LLC
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
// Golomb ruler problem
//
// find minimal ruler so that the differences between ticks are unique.
//
// First solutions:
// 0, 1
// 0, 1, 3
// 0, 1, 4, 6
// 0, 1, 4, 9, 11
// 0, 1, 4, 10, 12, 17
// 0, 1, 4, 10, 18, 23, 25
#include <cstdint>
#include <cstdio>
#include "absl/flags/flag.h"
#include "absl/flags/parse.h"
#include "absl/flags/usage.h"
#include "absl/strings/str_format.h"
#include "google/protobuf/text_format.h"
#include "ortools/base/integral_types.h"
#include "ortools/base/logging.h"
#include "ortools/sat/cp_model.h"
#include "ortools/sat/model.h"
ABSL_FLAG(bool, print, false, "If true, print the minimal solution.");
ABSL_FLAG(
int, size, 0,
"Size of the problem. If equal to 0, will test several increasing sizes.");
ABSL_FLAG(std::string, params, "", "Sat parameters.");
static const int kBestSolutions[] = {0, 1, 3, 6, 11, 17, 25, 34, 44, 55, 72, 85,
// just for the optimistics ones, the rest:
106, 127, 151, 177, 199, 216, 246};
static const int kKnownSolutions = 19;
namespace operations_research {
namespace sat {
void GolombRuler(int size) {
CHECK_GE(size, 1);
CpModelBuilder cp_model;
std::vector<IntVar> ticks(size);
ticks[0] = cp_model.NewConstant(0);
const int64_t max = size * size;
Domain domain(1, max);
for (int i = 1; i < size; ++i) {
ticks[i] = cp_model.NewIntVar(domain);
}
std::vector<IntVar> diffs;
for (int i = 0; i < size; ++i) {
for (int j = i + 1; j < size; ++j) {
const IntVar diff = cp_model.NewIntVar(domain);
cp_model.AddEquality(LinearExpr::Sum({diff, ticks[i]}), ticks[j]);
diffs.push_back(diff);
}
}
cp_model.AddAllDifferent(diffs);
// Symmetry breaking.
if (size > 2) {
cp_model.AddLessThan(diffs.front(), diffs.back());
}
// Objective.
cp_model.Minimize(ticks.back());
// Search strategy.
cp_model.AddDecisionStrategy(ticks, DecisionStrategyProto::CHOOSE_FIRST,
DecisionStrategyProto::SELECT_MIN_VALUE);
Model model;
SatParameters parameters;
parameters.set_search_branching(SatParameters::FIXED_SEARCH);
// Parse the --params flag.
if (!absl::GetFlag(FLAGS_params).empty()) {
CHECK(google::protobuf::TextFormat::MergeFromString(
absl::GetFlag(FLAGS_params), ¶meters))
<< absl::GetFlag(FLAGS_params);
}
model.Add(NewSatParameters(parameters));
const CpSolverResponse response = SolveCpModel(cp_model.Build(), &model);
if (response.status() == CpSolverStatus::OPTIMAL) {
const int64_t result = SolutionIntegerValue(response, ticks.back());
const int64_t num_failures = response.num_conflicts();
absl::PrintF("N = %d, optimal length = %d (conflicts:%d, time=%f s)\n",
size, result, num_failures, response.wall_time());
if (size - 1 < kKnownSolutions) {
CHECK_EQ(result, kBestSolutions[size - 1]);
}
if (absl::GetFlag(FLAGS_print)) {
for (int i = 0; i < size; ++i) {
const int64_t tick = SolutionIntegerValue(response, ticks[i]);
printf("%d ", static_cast<int>(tick));
}
printf("\n");
}
}
}
} // namespace sat
} // namespace operations_research
int main(int argc, char** argv) {
absl::SetFlag(&FLAGS_logtostderr, true);
google::InitGoogleLogging(argv[0]);
absl::ParseCommandLine(argc, argv);
if (absl::GetFlag(FLAGS_size) != 0) {
operations_research::sat::GolombRuler(absl::GetFlag(FLAGS_size));
} else {
for (int n = 1; n < 11; ++n) {
operations_research::sat::GolombRuler(n);
}
}
return EXIT_SUCCESS;
}