A Study of Multi-Objective Optimisation Algorithms

Peiqi Gao

2025

Abstract

In production activities, the problem often involves the optimisation of multiple objectives, and the traditional single-objective problem-solving methods are unable to deal with optimisation problems with multiple objectives. Traditional single-objective optimization methods usually focus on the optimal solution of one objective function, while multi-objective optimization problems need to consider multiple objective functions at the same time. This paper offers a comprehensive summary of the approaches to multi-objective optimization problems and proposes recommendations for future development. Firstly, the development history of multi-objective optimisation algorithms is reviewed, and then the related concepts of multi-objective problems, such as pareto optimal solution set, are briefly explained. In this paper, multi-objective optimisation algorithms are broadly classified into three categories: multi-objective weighting methods, multi-objective population genetic algorithms, and multi-objective individual evolutionary algorithms. The advantages and disadvantages of the three main types of methods are analysed by practical examples of the methods, and suggestions for subsequent improvements are given based on limitations.

Paper Citation

in Harvard Style

Gao P. (2025). A Study of Multi-Objective Optimisation Algorithms. In Proceedings of the 2nd International Conference on Data Science and Engineering - Volume 1: ICDSE; ISBN 978-989-758-765-8, SciTePress, pages 175-181. DOI: 10.5220/0013680600004670

in Bibtex Style

@conference{icdse25,
author={Peiqi Gao},
title={A Study of Multi-Objective Optimisation Algorithms},
booktitle={Proceedings of the 2nd International Conference on Data Science and Engineering - Volume 1: ICDSE},
year={2025},
pages={175-181},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013680600004670},
isbn={978-989-758-765-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Data Science and Engineering - Volume 1: ICDSE
TI - A Study of Multi-Objective Optimisation Algorithms
SN - 978-989-758-765-8
AU - Gao P.
PY - 2025
SP - 175
EP - 181
DO - 10.5220/0013680600004670
PB - SciTePress