GeoIPD

Inexact Penalty Decomposition Methods for Optimization Problems with Geometric Constraints

General Information

Code related to the paper

Kanzow, Christian, and Matteo Lapucci. "Inexact penalty decomposition methods for optimization problems with geometric constraints." Computational Optimization and Applications (2023): 1-35.

If you have used our code for research purposes, please cite the publication mentioned above. For the sake of simplicity, we provide the Bibtex format:

@article{kanzow2023inexact,
  title={Inexact penalty decomposition methods for optimization problems with geometric constraints},
  author={Kanzow, Christian and Lapucci, Matteo},
  journal={Computational Optimization and Applications},
  pages={1--35},
  year={2023},
  publisher={Springer}
}

Installation

In order to execute the code, you need an Anaconda environment. We provide YAML file in order to facilitate the installation of the latter.

For Linux user

Open a terminal in the project root folder and execute the following command.

conda env create -f geoipd.yml

Main Packages

• python v3.9
• numpy v1.22.3
• scipy v1.7.3
• matplotlib v3.5.2
• gurobipy v9.5.2

Gurobi Optimizer

In order to run some parts of the code, the Gurobi Optimizer needs to be installed and, in addition, a valid Gurobi licence is required. However, the employment of the Gurobi Optimizer is only required for a subset of experiments and test problems. The PD algorithm does not employ Gurobi, nor the implementations of sparisity and low rank constrained problems.

Usage

Run main.py (command python main.py in linux terminal) to test the code; comment/uncomment function calls at the end of the file to reproduce the different experiments reported in the paper.

Contact

If you have any question, feel free to contact me:

Matteo Lapucci
Global Optimization Laboratory (GOL)
University of Florence
Email: matteo dot lapucci at unifi dot it