Parameter Investigation in Brain Storm Optimization

Abstract

Human being is the most intelligent organism in the world and the brainstorming process popularly used by them has been demonstrated to be a significant and promising way to create great ideas for problem solving. Brain storm optimization (BSO) is a new kind of swarm intelligence algorithm inspired by human being creative problem solving process. BSO transplants the brainstorming process in human being into optimization algorithm design and gains successes. BSO generally uses the grouping, replacing, and creating operators to produce ideas as many as possible to approach the problem solution generation by generation. In these operators, BSO involves mainly three control parameters named: (1) p_replce to control the replacing operator; (2) p_one to control the creating operator to create new ideas between one cluster and two clusters; and (3) p_center (p_one_center and p_two_center) to control using cluster center or random idea to create new idea. In this paper, we make investigations on these parameters to see how they affect the performance of BSO. More importantly, a new BSO variant designed according to the investigation results is proposed and its performance is evaluated.