摘要
从分析粒子群算法的早熟现象的原因入手及受生物进化过程中突变和灾难现象的启发,在标准粒子群优化算法的基础上,提出一种群体消亡粒子群优化算法。将微粒分成大小相同的几个种群,在粒子群算法运行的适当时机,依一定方式使群体中的适当子群体消亡并随机补充新个体,以维持群体的适当规模和多样性。对Schaffer’s f 6函数的仿真结果表明,该算法易于找到全局最优解。将改进的算法应用于电磁继电器的优化设计之中,验证了其有效性。
Based on the analysis of reason for the premature convergence causing in particle swarm optimization（PSO）,and enlightened by the phenomenon of mutation and disaster in the biology evolution procession,a population disappearance particle swarm optimization was presented.The particles were divided into several swarms in the same size,a certain number of individuals disappeared after several iterations in every swarm,and the same number of new individuals were added to the swarms randomly to maintain the suitable swarm size.Simulation results of Schaffer’s f 6 function showed that the algorithm could easily find the global optimum solution.The improved PSO algorithm had been used for the optimal design of electromagnetic relay and the simulation results had verified the validation of the improved PSO.
出处
《低压电器》
北大核心
2011年第5期1-4,共4页
Low Voltage Apparatus
关键词
粒子群算法
优化设计
电磁继电器
particle swarm oplimization（pso）
optimal design
electromagnetic relay
