This is the unofficial implemented code in PyTorch for the paper "Neural Approximate Dynamic Programming for On-Demand Ride-Pooling" that appears in the Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence.
We recommend using python<=3.7 and a conda venv.
conda create --name NeurADP python=3.7
cd path/to/NeurADP
conda activate NeurADP
Install the dependencies with:
pip install -r requirements.txt
Pay attention to the installation of docplex
!
If you only want to use the free version of docplex
, simply:
pip install docplex
If you want to use the full version of docplex
, you need to install it from source. (or contact the developer)
git clone https://github.com/IBMDecisionOptimization/docplex-docplex.git
cd docplex-docplex
python setup.py install
When you're done working on the project, deactivate the conda virtual environment with deactivate
.
Here is the structure of the data folder:
data/
files_60sec/
test_flow_5000_1.txt
test_flow_5000_2.txt
ignorezonelist.txt
taxi_3000_final.txt
zone_path.csv
zone_traveltime.csv
To run the code, simply:
python main.py
The code will automatically process the data in the data
folder.