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动态环境下带有非线性效应的复合粒子群优化算法 被引量：4

Composite particle swarm optimization with nonlinear effect in dynamic environment
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摘要 针对粒子群优化算法在求解动态优化问题存在多样性缺失,寻优速度慢等缺陷,借鉴物理学中的非线性复合效应,本文提出带有非线性效应的复合粒子群优化算法,该算法利用复合材料的相乘效应根据粒子的相似性,基于"最坏优先"规则将种群划分成若干复合粒子.为使种群迅速地在动态环境中找到最优解,利用复合材料的共振效应,成员粒子通过自适应异速度映射机制整合有价值信息.为提高种群的多样性,利用复合材料的诱导效应,引入复合粒子的整体运动策略.最后通过动态标准测试问题实验对相关参数设置进行了分析,并与其他几种粒子群算法相比较,验证了该算法在动态环境中的有效性. This paper presents a new particle swarm optimization model,called composite particle swarm optimization with nonlinear effect（CPSO–NE）,to deal with dynamic optimization problems.CPSO–NE partitions the swarm into a set of composite particles based on their similarity using a ＂worst-first＂ principle.Inspired by the notion of the composite particle phenomenon in physics,the elementary members in each composite particle interact via a velocity-anisotropic reflection scheme to integrate valuable information for effectively and rapidly finding the promising optima in the search space.Each composite particle maintains the diversity by a scattering operator.In addition,an integral movement strategy is introduced to promote the swarm diversity.Experiments on a typical dynamic test benchmark problem provide a guideline for setting the involved parameters and show that CPSO–NE is efficient in comparison with several state-of-the-art PSO algorithms for dynamic optimization problems.
作者 刘黎黎 李国家 汪定伟
机构地区 中石油东北炼化工程有限公司 东北大学信息科学与工程学院流程工业综合自动化重点实验室
出处 《控制理论与应用》 EI CAS CSCD 北大核心 2012年第10期1253-1262,共10页 Control Theory & Applications
基金 国家自然科学基金资助项目(70931001 70771021 70721001) 国家自然科学基金创新研究群体科学基金资助项目(60521003 60821063) 国家自然科学基金青年基金资助项目(61004121 71001018)
关键词 粒子群优化 复合粒子 异速度映射 自适应步长调整 动态优化问题 particle swarm optimization（PSO） composite particle velocity-anisotropic reflection self-adaptive stepsize adjustment dynamic optimization problem
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24

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二级参考文献30

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共引文献73

同被引文献45

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控制理论与应用
2012年 第10期

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