A model-based algorithm for the fair-capacitated clustering problem.
The MPFCC-Algorithm depends on:
Gurobi is a commercial mathematical programming solver. Free academic licenses are available here. The other dependencise are included in the requirements.txt file.
- Download and install Gurobi (https://www.gurobi.com/downloads/)
- Clone this repository (git clone https://github.com/phil85/MPFCC-Algorithm.git)
- Install the dependencies (pip install -r requirements.txt)
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)
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}}
This project is licensed under the MIT License - see the LICENSE file for details