Modified Social-Spider Optimization Algorithm Applied to Electromagnetic Optimization

Social-spider optimization (SSO) is a new nature-inspired algorithm of the swarm intelligence field to global optimization applications, which is based on the simulation of cooperative behavior of social spiders. To enhance the performance of the standard SSO, a modified SSO (MSSO) approach based on beta distribution and natural gradient local search was proposed in this paper. In order to verify the performance of the MSSO, tests using Loney's solenoid benchmark and a brushless direct current motor benchmark are realized comparing the effectiveness of the SSO and the proposed MSSO. The results of this paper demonstrated that the MSSO performance is promising in electromagnetics optimization.