An Improved Brainstorm Optimization Algorithm Based on the Strategy of Random Perturbation and Vertical Variation
Gang Bao, Jie Li, Run-tao Huang, Ke-xin Shen · 2019
The brainstorming optimization algorithm (BSO) is a swarm intelligence algorithm based on human creative thinking, which is inspired by the brainstorming process and proposed by Professor Yuhui Shi. It has been successfully applied to a lot of engineering problems involving optimization. In this paper, random perturbation strategy and vertical crossover variation are introduced to BSO to improve its performance. The specific idea is to increase the random disturbance and the vertical cross variation on the same variable when the individual is updated. The proposed algorithm Accelerating BSO (ABSO) is compared with BSO and other three algorithms(PSO, DE, CS) on 9 benchmark functions. From the results, both final solutions and convergence speed show the superiority of ABSO.