A Review of Glowworm Swarm Optimization Meta-Heuristic Swarm Intelligence and its Fusion in Various Applications

Muhammad A. S. Mohd Shahrom, Nurezayana, Mohamad F. Ab. Aziz, Salama A. Mostafa
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引用次数: 1

Abstract

Natural phenomena inspire the meta-heuristic algorithm to carry out the aim of reaching the optimal solution. Glowworm swarm optimization (GSO) is an original swarm intelligence algorithm for optimization, which mimic the glow behavior of glowworm that can effectively capture the maximum multimodal function. GSO is part of the meta-heuristic algorithm used to solve the optimization problem. This algorithm solves many problems in optimization, especially in science, engineering, and network. Therefore, this paper review exposes the GSO method in solving the problem in any industry area. This study focuses on the basic flow of GSO, the modification of GSO, and the hybridization of GSO by conducting the previous study of the researcher. Based on this study, the GSO application in the engineering industry gets the highest score of 15% among other sectors.
萤火虫群优化元启发式群体智能及其融合应用综述
自然现象启发了元启发式算法来实现达到最优解的目标。萤火虫群优化算法(GSO)是一种新颖的群体智能优化算法,它模拟萤火虫的发光行为,能够有效地捕获最大的多模态函数。GSO是用于解决优化问题的元启发式算法的一部分。该算法解决了许多优化问题,特别是在科学、工程和网络领域。因此,本文综述了GSO方法在解决任何行业问题中的应用。本研究通过开展研究者前期的研究,重点研究了GSO的基本流程、GSO的改性以及GSO的杂交。基于本研究,GSO在工程行业的应用在其他行业中得分最高,为15%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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