A demo on how to use column generation within a heuristic for solving the Vehicle Routing Problem with Time Windows (VRPTW). Companion repo for the medium article "How to Implement Column Generation for Vehicle Routing".
This package recreates its environment from conda and requires a Gurobi license to run. After installing both, clone this repo and do the following:
cd <path/to/cloned/repo>
conda env create -f environment.yml
conda activate col_gen
cd vehicle_routing_column_generation
python algorithms.py
To run this from your own CSV data, check out tutorial/csv_example.py for an
example on how to do so.
Where the algorithms and data requirements for solving the VRPTW live. You can also find notes on how to tune parameters here.
The test suite for vehicle_routing_column_generation can be found here.
This is the source for the gists embedded in the medium article about this repo.
This is the source and a .pdf rendering of a presentation I made based off the medium article.
This is a package for creating and running numerical experiments that compare the solution quality of exact and heuristic solves of the VRP. I used this package to demonstrate how column generation heuristics can find nearly optimal solutions to the VRPTW in less time than exact solves. It also demonstrates how to run experiments in parallel on server clusters running torque, as I used that demo to my Ph.D. program as the excuse to get to write the rest of this project.