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CombOptNet: Fit the Right NP-Hard Problem by Learning Integer Programming Constraints

This repository contains PyTorch implementation of the paper CombOptNet: Fit the Right NP-Hard Problem by Learning Integer Programming Constraints

Installation

1. Run pipenv install (at your own risk with --skip-lock to save some time).
2. From within the pipenv environment run python3 -m pip install -i https://pypi.gurobi.com gurobipy.
3. Obtain a license and download/set it.
4. Download and extract the datasets.

Usage

For [experiment] = knapsack or [experiment] = static_constraints:

1. Set the base_dataset_path parameter in experiments/[experiment]/base.yaml.
2. In case of static constraints: set the dataset_specification parameter in experiments/static_constraints/base.yaml
3. Run python3 main.py experiments/[experiment]/[method].yaml.

Citation

@misc{paulus2021comboptnet,
      title={CombOptNet: Fit the Right NP-Hard Problem by Learning Integer Programming Constraints}, 
      author={Anselm Paulus and Michal Rolínek and Vít Musil and Brandon Amos and Georg Martius},
      year={2021},
      eprint={2105.02343},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}