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协调粒子群优化算法--HPSO
引用本文:潘峰,涂序彦,陈杰,付继伟.协调粒子群优化算法--HPSO[J].计算机工程,2005,31(1):169-171.
作者姓名:潘峰  涂序彦  陈杰  付继伟
作者单位:北京理工大学信息科学技术学院自动控制系,北京,100081
摘    要:粒子群优化算法(PSO)是模拟生物群体智能的优化算法、具有良好优化性能。但是由于信息的单一传递,群体的迅速收缩和群体多样性降低,导致算法早熟收敛.该文采用多样性控制与交叉操作,使粒子群在细化搜索与扩展新区之间进行协调,提出了协调粒子群优化算法HPSO。实验结果表明:HPSO比PSO有更好的性能。

关 键 词:协调粒子群优化算法  多样性  交叉算子  伪星型拓扑结构
文章编号:1000-3428(2005)01-0169-03

A Harmonious Particle Swarm Optimizer --HPSO
PAN Feng,TU Xuyan,CHEN Jie,FU Jiwei.A Harmonious Particle Swarm Optimizer --HPSO[J].Computer Engineering,2005,31(1):169-171.
Authors:PAN Feng  TU Xuyan  CHEN Jie  FU Jiwei
Abstract:Particle swarm optimization(PSO) algorithm is a new population intelligence based algorithm and exhibits good performance on optimization. However the algorithm will fall into premature convergence due to the decrease of population diversity, caused by the simplex information spread and fast convergence of population. In this paper, crossover operator and diversity control factor are introduced to keep the harmony between attraction (searching in detail) and expand (explore a new area). Experiments on benchmark functions shows HPSO outperform standard PSO.
Keywords:Harmonious particle swarm optimizer(HPSO)  Diversity  Crossover operator  Pseudo-star topology  
本文献已被 CNKI 维普 万方数据 等数据库收录!
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