UCLA

Brain Storm Optimization (BSO) is a swarm intelligence optimization algorithm inspired by the collective behavior of human beings in solving problems, i.e., brainstorming process. The algorithm was proposed by Y. Shi in 2011 inspired by such a behavior. Brainstorming is used when there is a difficult problem that cannot be solved by a single individual. Based on several tests, BSO has demonstrated great results to be a powerful optimization tool that can be used in electromagnetics and antenna engineering. To the best of our knowledge, this is the first time that BSO is applied to electromagnetic problem. BSO has been applied to common mathematical benchmark functions, the standard method of testing optimization algorithms. For electromagnetics and antenna applications, several representative examples such as a Yagi-Uda antenna, a Luneburg lens and others have been optimized using both BSO and PSO. Also, a design was optimized, prototyped and measured. Additionally, a novel binary version of BSO is proposed and applied with success to multiple antenna designs.