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电子学报  2013 

一种精英反向学习的粒子群优化算法

DOI: 10.3969/j.issn.0372-2112.2013.08.031, PP. 1647-1652

Keywords: 全局优化,粒子群优化,精英反向学习,差分演化变异,群体选择

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Abstract:

为解决传统粒子群优化算法易出现早熟的不足,提出了精英反向学习策略,引入精英粒子,采用反向学习生成其反向解,扩大搜索区域的范围,可增强算法的全局勘探能力.同时,为避免最优粒子陷入局部最优而导致整个群体出现搜索停滞,提出了差分演化变异策略,采用差分演化算法搜索最优粒子的邻域空间,可增强算法的局部开采能力.在14个测试函数上将本文算法与多种知名的PSO算法进行对比,实验结果表明本文算法在解的精度与收敛速度上更优.

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