Implementation of the FD framework proposed in
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:
@misc{lapucci2024effective,
title={Effective Front-Descent Algorithms with Convergence Guarantees},
author={Matteo Lapucci and Pierluigi Mansueto and Davide Pucci},
year={2024},
eprint={2405.08450},
archivePrefix={arXiv},
primaryClass={math.OC}
}
In order to execute the code, you need an Anaconda environment and the Python packages nsma, pymoo installed in it. For a detailed documentation of the nsma package we refer the reader to its GitHub repository, while for the pymoo package we refer to the website.
For the packages installation, open a terminal (Anaconda Prompt for Windows users) in the project root folder and execute the following commands. Note that a Python version 3.10.6 or higher is required.
pip install nsma
pip install pymoo
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.
In parser_management.py you can find all the possible arguments. Given a terminal (Anaconda Prompt for Windows users), an example of execution could be the following.
python main.py --algs FD_BB --probs JOS --plot_pareto_front --plot_pareto_solutions --general_export --export_pareto_solutions --FD_eps_hv 0.0001
If you have any question, feel free to contact us:
Pierluigi Mansueto, Davide Pucci
Global Optimization Laboratory (GOL)
University of Florence
Email: pierluigi dot mansueto at unifi dot it, davide dot pucci at unifi dot it