lmop

https://github.com/antonioornatelli/lmop

Science Score: 44.0%

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Low similarity (11.9%) to scientific vocabulary

Last synced: 10 months ago · JSON representation ·

Repository

Basic Info

Host: GitHub
Owner: AntonioOrnatelli
License: mit
Language: Python
Default Branch: main
Size: 15.6 KB

Statistics

Stars: 0
Watchers: 1
Forks: 1
Open Issues: 0
Releases: 0

Created over 1 year ago · Last pushed over 1 year ago

Metadata Files

Readme License Citation

Weighting Method for Non-Preemptive Multi-Objective Mathematical Programming

This repository contains the code supporting the paper Weighting Method for Non-Preemptive Multi-Objective Mathematical Programming by L. Ferro, G. Filaci, A. Manzini, A. Ornatelli. This code has been used to produce the results presented in the section Numerical Results of the paper.

The code includes a Python implementation of the weighting method (problems/multi_objective_problem.py) and a script (main.py) which can be used to apply it to two given families of Lexicographic Multi-Objective Problems: a kite in 2D with 3 objectives and a randomly rotated hypercube in 200D with 200 objectives. The single-objective problems derived from the LMOPs are then solved using the free and publicly available community edition of the commercial solver CPLEX.

Since the aim of these experiments is to compare the performance of our novel method to the one by Cococcioni et al., 2020 [1], the same problems described in that paper are reconstructed and solved here.

Usage

Prerequisites

The code has been tested and executed on Python 3.10.15 running on an Apple M3 Pro with a 12-core CPU (6 performance cores up to 4.06 GHz and 6 efficiency cores up to 2.8 GHz). It may work on other versions of Python and produce comparable results on different hardware.

Installation

Install the required packages by running: bash pip install -r requirements.txt

Running the Code

To run the code, simply execute the script main.py:bash python main.py`

The script will run and print the timing and the results of the experiments on the two families of problems.

References

[1] Cococcioni, M., Cudazzo, A., Pappalardo, M., and Sergeyev, Y. D. (2020). Solving the lexicographic multi-objective mixed-integer linear programming problem using branch-and-bound and grossone methodology. Communications in Nonlinear Science and Numerical Simulation, 84:105177.

License

This code is released under the MIT License. See the LICENSE file for more information.

Owner

Login: AntonioOrnatelli
Kind: user

Repositories: 2
Profile: https://github.com/AntonioOrnatelli

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
  - family-names: Ornatelli
    given-names: Antonio
    orcid: https://orcid.org/0000-0002-2346-7645
  - family-names: Manzini
    given-names: Andrea
  - family-names: Filaci
    given-names: Gianluca
    orcid: https://orcid.org/0000-0002-9453-7161
  - family-names: Ferro
    given-names: Leonardo
title: "Numerical examples for Lexicographic Multi-Objective Optimization solution method"
url: "https://github.com/AntonioOrnatelli/LMOP"
version: 1.0
date-released: 2025-01-17

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Last synced: 10 months ago

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