Amazon Last-Mile Challenge

Code maintainer： Wentao Zhao (wz2543@columbia.edu)

Code contributors: Chen Jing, Yunhao Xing, Wentao Zhao

This code is for the Amazon last-mile research challenge.

We realized an attention model in the Transformer architecture for route optimization problems under realistically sized problem instances. The training is done via reinforcement learning and imitation learning.

Dependencies

• Python>=3.8
• NumPy
• SciPy
• PyTorch
• torch-geometric
• tqdm

Usage

python src/train.py

Acknowledgements

This repository is built based on the following repositories:

• https://github.com/wouterkool/attention-learn-to-route
• https://github.com/Hanjun-Dai/graph_comb_opt

For more details, please see the papers Attention, Learn to Solve Routing Problems!, Learning Combinatorial Optimization Algorithms over Graphs.

@article{kool2018attention,
  title={Attention, learn to solve routing problems!},
  author={Kool, Wouter and Van Hoof, Herke and Welling, Max},
  journal={arXiv preprint arXiv:1803.08475},
  year={2018}
}

@article{dai2017learning,
  title={Learning combinatorial optimization algorithms over graphs},
  author={Dai, Hanjun and Khalil, Elias B and Zhang, Yuyu and Dilkina, Bistra and Song, Le},
  journal={arXiv preprint arXiv:1704.01665},
  year={2017}
}