Enhancing Many-Objective Particle Swarm Optimization with Island Model for Agricultural Optimization

Chnini Samia, Abadlia Houda, Smairi Nadia, Nasri Nejah

2025

Abstract

With the growing complexity of agricultural systems and the need to optimize multiple conflicting objectives simultaneously, traditional optimization methods often struggle to find satisfactory solutions. In this work, we introduce a novel enhancement to the standard Multi Objectives Particle Swarm Optimization (MOPSO) algorithm that significantly improves its effectiveness in handling the diverse and dynamic objectives inherent in agricultural optimization problems. we propose an improvement to the MOPSO algorithm by introducing an islanding technique to promote exploration and exploitation of the many-objective search space. The improved MOPSO algorithm, called I-MOPSO guide the search towards optimal and diverse solutions by dividing the search space into islands and facilitating information exchange between them. We put I-MOPSO into practice and tested it using a series of common many objective optimization algorithms. According to Experimental results show that I-MOPSO is capable of finding high-quality solutions on a variety of test problems, often outperforming the standard MOPSO algorithm and NSGAIII.

Paper Citation

in Harvard Style

Samia C., Houda A., Nadia S. and Nejah N. (2025). Enhancing Many-Objective Particle Swarm Optimization with Island Model for Agricultural Optimization. In Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART; ISBN 978-989-758-737-5, SciTePress, pages 608-615. DOI: 10.5220/0013315200003890

in Bibtex Style

@conference{icaart25,
author={Chnini Samia and Abadlia Houda and Smairi Nadia and Nasri Nejah},
title={Enhancing Many-Objective Particle Swarm Optimization with Island Model for Agricultural Optimization},
booktitle={Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART},
year={2025},
pages={608-615},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013315200003890},
isbn={978-989-758-737-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART
TI - Enhancing Many-Objective Particle Swarm Optimization with Island Model for Agricultural Optimization
SN - 978-989-758-737-5
AU - Samia C.
AU - Houda A.
AU - Nadia S.
AU - Nejah N.
PY - 2025
SP - 608
EP - 615
DO - 10.5220/0013315200003890
PB - SciTePress