This repository is the official implementation of the paper: Interior Point Solving for LP-based prediction+optimisation
@inproceedings{lpinterior2020,
author = {Jayanta Mandi and Tias Guns},
title={Interior Point Solving for LP-based prediction+optimisation},
booktitle={Advances in Neural Information Processing Systems},
year = {2020}
}
- Pandas
- Numpy
- Gurobipy
- PyTorch
- Scipy
- scikit-learn
- qpth
- CVXPY
The Forward pass of the algorithm is derived from https://github.com/scipy/scipy/tree/master/scipy/optimize
To run the experiment of Building Knapsack, go to the directory experiments/Building Knapsack/ and then run ModelRun.py
cd experiments/Building Knapsack/
python ModelRun.py
To run the experiment of Energy-cost aware scheduling, go to the directory experiments/EnergyScheduling/ and then run exp_run.py
To run the experiment of Shortest path problem, go to the directory experiments/Twitter Shortest Path/ and unzip the data and then run exp_run.py
cd experiments/Twitter\ Shortest\ Path/
unzip data.zip
python exp_run.py