三群协同粒子群优化算法
Three Swarms Cooperative Particle Swarm Optimization
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摘要: 针对基本粒子群优化算法易陷入局部极值点、搜索精度低等缺点,提出了一种三群协同粒子群优化算法(TSC-PSO)。搜索时,如果全局极值连续若干代没有改善,粒子未找到全局最优点,就任选某个优群,将其群内粒子和差群粒子交换。仿真结果显示,对一些经典多峰值函数、非凸病态函数,TSC-PSO增强了全局搜索能力,具有比基本PSO更好的优化性能。Abstract: In order to overcome the drawback of basic PSO,such as being subject to falling into local optimization and being poor in performance of precision,an improved PSO algorithm,three swarms(cooperative) particle swarm optimization(TSC-PSO),is proposed.Regarding to several special multimodal functions and singular non-convex functions,the results of simulation show that the TSC-PSO can strengthen the global searching ability and have better optimization performance than basic PSO.