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一种新的混合粒子群方法
引用本文:管月智,葛洪伟. 一种新的混合粒子群方法[J]. 计算机工程与应用, 2011, 47(23): 45-47
作者姓名:管月智  葛洪伟
作者单位:江南大学 信息工程学院,江苏 无锡 214122
摘    要:利用混沌搜索和变异机制克服种群易停滞且易陷入局部最优点的不足。当种群出现停滞时先用混沌搜索更优点,当搜索到的点不满足变异精度要求时再进行变异。发现混沌搜索能使种群在出现停滞时持续寻优,而变异机制则能够有效地帮助种群在陷入局部最优点时跳出该点。结果表明该方法的全局寻优能力较强。

关 键 词:混沌  变异  粒子群优化  变异机制  
修稿时间: 

New hybrid particle swarm optimization
GUAN Yuezhi,GE Hongwei. New hybrid particle swarm optimization[J]. Computer Engineering and Applications, 2011, 47(23): 45-47
Authors:GUAN Yuezhi  GE Hongwei
Affiliation:School of Information and Technology,Jiangnan University,Wuxi,Jiangsu 214122,China
Abstract:By introducing chaotic search and mutation mechanism,population can overcome the shortcomings of stagnation and trapping into local optimums.When the population is stagnation,chaotic search is used to find a better point firstly.If this point does not meet the precision of mutation,then mutation mechanism will make effort.Chaotic search can continuously optimize when the population is stagnation,mutation mechanism helps the population break away from local optimum when it has trapped into the local optimum.Experimental results show that the new algorithm is relatively obvious for the ability of global optimization.
Keywords:chaos  mutation  particle swarm optimization  mutation mechanism
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