Using Grey Wolf Hunting Mechanism to Improve Brain Storm Optimization

Brain storm optimization algorithm (BSO) is recently proposed population based optimization algorithm, which is inspired by the human brainstorming process. It is designed to solve global optimization problems and has a good performance in solving large-scale multidimensional multimodal problems. However, as it largely relies on the cluster center to update the population which makes it hard to exchange information within population, it can be frequently fall into the local optimal and can't get rid of this situation easily. Grey wolf optimization (GWO) algorithm has good abilities of global search and local area avoidance, thus, GWO is studied and combined with BSO to improve its ability of global search and avoid local optimal. The experiment results on CEC'17 benchmark function indicate the feasibility of this combination.