Metaheuristic optimization algorithms: An overview

issue 14(1)2024
Published Feb 5, 2024
https://doi.org/10.46223/HCMCOUJS.acs.en.14.1.47.2024
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Received: 2023-11-06
Accepted: 2024-01-22
Published: 2024-02-05
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Brahim Benaissa - benaissa@toyota-ti.ac.jp
Toyota Technological Institute, Nagoya, Japan
Masakazu Kobayashi
Toyota Technological Institute, Nagoya, Japan
Musaddiq Al Ali
Toyota Technological Institute, Nagoya, Japan
Tawfiq Khatir
University Centre Salhi Ahmed Naama, Naama, Algeria
Mohamed El Amine Elaissaoui Elmeliani
The University of Kitakyushu, Fukuoka, Japan

Abstract

Metaheuristic optimization algorithms are versatile and adaptable tools that effectively solve various complex optimization problems. These algorithms are not restricted to specific types of problems or gradients. They can explore globally and handle multi-objective optimization efficiently. They strike a balance between exploration and exploitation, contributing to advancements in optimization. However, it’s important to note their limitations, including the lack of a guaranteed global optimum, varying convergence rates, and their somewhat opaque functioning. In contrast, metaphor-based optimization algorithms, while intuitively appealing, have faced controversy due to potential oversimplification and unrealistic expectations. Despite these considerations, metaheuristic algorithms continue to be widely used for tackling complex problems. This research paper aims to explore the fundamental components and concepts that underlie optimization algorithms, focusing on the use of search references and the delicate balance between exploration and exploitation. Visual representations of the search behavior of selected metaheuristic algorithms will also be provided.

Keywords

exploration, exploitation, optimization, metaheuristic, review

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Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

How to Cite
Benaissa, B., Kobayashi, M., Al Ali, M., Khatir, T., & El Amine Elaissaoui Elmeliani, M. (2024). Metaheuristic optimization algorithms: An overview. HCMCOU Journal of Science – Advances in Computational Structures, 14(1), 33–61. https://doi.org/10.46223/HCMCOUJS.acs.en.14.1.47.2024
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