A Hierarchical Subpopulation Particle Swarm Optimization Algorithm

摘要

Based on the metaphor of specialization and cooperation in hierarchical social organization, a new particle swarm optimization (PSO) algorithm, hierarchical subpopulation PSO (HS-PSO), is proposed. In HS-PSO, the entire population is divided into several subpopulations which are arranged in a hierarchy. The subpopulations at the same level of the hierarchy evolve relative independently and cooperate with each other via their respective best particles. For the particles at different levels, different tasks are assigned. Two versions of HS-PSO which use the same or different kinds of PSO algorithms for the particles at different levels are presented. The efficiency of HS-PSO is verified by the simulation results.