Particle Swarm Optimizer Networks with Stochastic Connection for Improvement of Diversity Search Ability to Solve Multimodal Optimization Problems

抄録

Particle swarm optimizer network (PSON) is one of the multi-swarm PSOs. In PSON, a population is divided into multiple sub-PSOs, each of which searches a solution space independently. Although PSON has a good solving performance, it may be trapped into a local optimum solution. In this paper, we introduce into PSON a dynamic stochastic network topology called “PSON with stochastic connection” (PSON-SC). In PSON-SC, each sub-PSO can be connected to the global best (gbest) information memory and refer to gbest stochastically. We show clearly herein that the diversity of PSON-SC is higher than that of PSON, while confirming the effectiveness of PSON-SC by many numerical simulations.