LeoWarnow / HyPaD

Implementation of the Hybrid Patch Decomposition Algorithm - a solver for multi-objective mixed-integer convex optimization problems

Home Page:https://doi.org/10.1007/s00186-023-00828-x

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HyPaD

This repository contains a Matlab and a Python implementation of the Hybrid Patch Decomposition Algorithm to solve multi-objective mixed-integer convex optimization problems.

Getting Started

You can start using HyPaD by downloading or cloning this repository using the green button near the top of the GitHub page. Then, just open the UserFile.m to access the Matlab implementation or the UserFile.ipynb for a Jupyter Notebook to access the Python implementation. Both serve as an interface to AdEnA and provide all instructions that you need to get started.

References

As this implementation is based on the scientific work by Gabriele Eichfelder and Leo Warnow, please cite the corresponding paper when using this code:

@Article{EW2023,
  author    = {Gabriele Eichfelder and Leo Warnow},
  journal   = {Mathematical Methods of Operations Research},
  title     = {A hybrid patch decomposition approach to compute an enclosure for multi-objective mixed-integer convex optimization problems},
  year      = {2023},
  doi       = {10.1007/s00186-023-00828-x},
  publisher = {Springer},
}

About

Implementation of the Hybrid Patch Decomposition Algorithm - a solver for multi-objective mixed-integer convex optimization problems

https://doi.org/10.1007/s00186-023-00828-x

License:MIT License


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Language:Python 57.0%Language:MATLAB 41.3%Language:Jupyter Notebook 1.7%