Fusion: Practice and Applications FPA 2692-4048 2770-0070 10.54216/FPA https://www.americaspg.com/journals/show/2043 2018 2018 Faculty of Computer Science and Information Technology, University Tun Hussein Onn Malaysia, 86400 Parit Raja, Batu Pahat, Johor, Malaysia Muhammad A. S. Mohd Shahrom Faculty of Computer Science and Information Technology, University Tun Hussein Onn Malaysia, 86400 Parit Raja, Batu Pahat, Johor, Malaysia Nurezayana .. Faculty of Computer Science and Information Technology, University Tun Hussein Onn Malaysia, 86400 Parit Raja, Batu Pahat, Johor, Malaysia Mohamad F. Ab. Aziz Faculty of Computer Science and Information Technology, University Tun Hussein Onn Malaysia, 86400 Parit Raja, Batu Pahat, Johor, Malaysia Salama A. Mostafa 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. 2023 2023 89 102 10.54216/FPA.130107 https://www.americaspg.com/articleinfo/3/show/2043