%0 Journal Article
%T MQPSO:Quantum-behaved Particle Swarm Optimization Based on Multi-swarm and Multi-phase Algorithm<br>MQPSO: 一种具有多群体与多阶段的QPSO算法*
%A ZHANG Chun-yan
%A XU Wen-bo
%A SUN Jun
%A GUAN Fang-jing
%A <br>张春燕
%A 须文波
%A 孙俊
%A 管芳景
%J 计算机应用研究
%D 2007
%I 
%X This paper introduced a improved Quantum-behaved Particle Swarm Optimization Algorithm,Multi-swarm and Multi-phase Quantum-behaved Particle Swarm Optimization(MQPSO).In this algorithm,it divides the whole particle swarm into different groups and searchs in different phases.It avoids particle prematurity and improves global search performance.The results of several improtant test functions confirm that the convergent performance of MQPSO outperforms Particle Swarm Optimization(PSO) algorithm and Quantum-behaved Particle Swarm Optimization algorithm.
%K particle swarm optimization algorithm
%K quantum-behave
%K global convergence
%K particle prematurity<br>粒子群算法
%K 量子行为
%K 全局收敛
%K 早熟
%K 多群体
%K 多阶段
%K 粒子群算法
%K Algorithm
%K Based
%K Standard
%K 标准
%K 测试结果
%K 测试函数
%K 收敛性能
%K 搜索
%K 利用
%K 粒子群优化算法
%K 量子行为
%K Particle
%K Swarm
%K Optimization
%K 改进
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=343459AF1736CA697BC21A9257E8EE79&yid=A732AF04DDA03BB3&vid=B91E8C6D6FE990DB&iid=38B194292C032A66&sid=8C83C265AD318E34&eid=331211A5F5616413&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=1&reference_num=8