MPFCC-Algorithm

A model-based algorithm for the fair-capacitated clustering problem.

Dependencies

The MPFCC-Algorithm depends on:

• Gurobi

Gurobi is a commercial mathematical programming solver. Free academic licenses are available here. The other dependencise are included in the requirements.txt file.

Installation

1. Download and install Gurobi (https://www.gurobi.com/downloads/)
2. Clone this repository (git clone https://github.com/phil85/MPFCC-Algorithm.git)
3. Install the dependencies (pip install -r requirements.txt)

Usage

The main.py file contains code that applies the MPFCC-algorithm to an illustrative example.

labels = mpfcc(X, colors, number_of_clusters, max_cardinality, min_balance,
               random_state=2, mpfcc_time_limit=300)

Reference

Please cite the following paper if you use this algorithm.

Tran, V.; Kammermann, M.; Baumann, P. (2023): The MPFCC algorithm: A model-based approach for fair-capacitated clustering. In: Proceedings of the 2023 IEEE International Conference on Industrial Engineering and Engineering Management. Singapore, 0677-0681

Bibtex:

@inproceedings{tran2023mpfcc,
  author={Tran, Vanessa and Kammermann, Manuel and Baumann, Philipp},
  booktitle={2023 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)}, 
  title={The MPFCC Algorithm: A Model-Based Approach for Fair-Capacitated Clustering}, 
  year={2023},
  pages={0677-0681},
  doi={10.1109/IEEM58616.2023.10406388}}

License

This project is licensed under the MIT License - see the LICENSE file for details