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基于等级熵的自适应粒子群优化算法 被引量：2

Rank entropy-based adaptive particle swarm optimization algorithm
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摘要 分析了粒子群耗散结构的特性,提出了基于等级熵的自适应粒子群优化(EPSO)算法.在演化过程的前期,针对粒子群优化(PSO)算法具有收敛速度慢、等级熵较大等特点,EPSO采用精英多父体杂交算子来提高算法的收敛速度,使群体形成有序的耗散结构.随着熵的减少,EPSO产生一个微小的混沌给予系统一个外界的负熵,使演化过程向更优适应值的方向发展.数值实验结果表明,该算法具有收敛精度高和收敛速度快的特点,可快速有效地求解某些优化问题. A rank entropy based particle swarm optimization EPSO） is proposed by analyzing the characteristic of the dissipative structure of the particle swarm. In the early evolution process, PSO has characteristics of slow convergence velocity and maximal rank entropy. EPSO adopts elite multi- parents crossover operator to improve convergence speed. With the decreasing of the rank entropy, swarm constructs orderly dissipative structure. EPSO introduces negative entropy through additional chaos so as to driving the irreversible evolution process with better fitness. Application of the EPSO to several optimization problems shows the EPSO algorithm holds the fast convergence velocity and good precise. EPSO algorithm can effectively and quickly solves some optimization problems.
作者 郭京蕾 吴志健 张建伟
机构地区 武汉大学软件工程国家重点实验室 华中师范大学计算机科学系
出处 《华中科技大学学报（自然科学版）》 EI CAS CSCD 北大核心 2009年第4期65-68,共4页 Journal of Huazhong University of Science and Technology(Natural Science Edition)
基金 国家重点基础研究发展计划资助项目(2007CB31080)
关键词 等级熵 精英多父体杂交算子 耗散结构 负熵 粒子群优化 rank entropy elite multi-parents crossover operator dissipative structure negative entropy particle swarm optimization （PSO）
分类号 TP301.6 [自动化与计算机技术—计算机系统结构]
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参考文献11

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共引文献605

同被引文献24

  • 1胡旺,李志蜀.一种更简化而高效的粒子群优化算法[J].软件学报,2007,18(4):861-868. 被引量：334
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引证文献2

二级引证文献10

华中科技大学学报（自然科学版）
2009年 第4期

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