Mutation and memory mechanism for improving Glowworm Swarm Optimization algorithm
Atheer Bassel, Md Jan Nordin · 2017
The Glowworm Swarm Optimization (GSO) is a population-based metaheuristic algorithm for optimization problems. Limitations of GSO are shown at the convergence speed and a weakness in the capability of global search which need to be improved. Thus, Memory Mechanism and Mutation for Glowworm Swarm Optimization (MMGSO) are proposed in this study to improve the GSO performance at the reported aspects. The proposed method is examined on Unimodal and Multimodal benchmark functions to prove the productivity of the MMGSO algorithm regarding to three metrics which are solution quality, convergence speed and robustness. The results of MMGSO are analyzed and compared with the basic GSO to show the efficiency of the proposed method.