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Multispecies Coevolution Particle Swarm Optimization Based on Previous Search History
Wang DP(王丹萍); Hu KY(胡琨元); Ma LB(马连博); He MW(何茂伟); Chen HN(陈瀚宁)
作者部门数字工厂研究室
发表期刊DISCRETE DYNAMICS IN NATURE AND SOCIETY
ISSN1026-0226
2017
卷号2017页码:1-22
收录类别SCI
WOS记录号WOS:000404398000001
产权排序1
资助机构Liaoning Province Education Administration [L2015360, L2014473, L2015372] ; Tianjin Province Science and Technology Projects [16ZLZDZF00150] ; National Natural Science Foundation of China [61603261, 61503373, 61602343, 51607122]
摘要A hybrid coevolution particle swarm optimization algorithm with dynamic multispecies strategy based on k-means clustering and nonrevisit strategy based on Binary Space Partitioning fitness tree (called MCPSO-PSH) is proposed. Previous search history memorized into the Binary Space Partitioning fitness tree can effectively restrain the individuals' revisit phenomenon. The whole population is partitioned into several subspecies and cooperative coevolution is realized by an information communication mechanism between subspecies, which can enhance the global search ability of particles and avoid premature convergence to local optimum. To demonstrate the power of the method, comparisons between the proposed algorithm and state-of-the-art algorithms are grouped into two categories: 10 basic benchmark functions (10-dimensional and 30-dimensional), 10 CEC2005 benchmark functions (30-dimensional), and a real-world problem (multilevel image segmentation problems). Experimental results show that MCPSO-PSH displays a competitive performance compared to the other swarm-based or evolutionary algorithms in terms of solution accuracy and statistical tests.
语种英语
WOS标题词Science & Technology ; Physical Sciences
WOS类目Mathematics, Interdisciplinary Applications ; Multidisciplinary Sciences
关键词[WOS]DIFFERENTIAL EVOLUTION ; MULTIPLE OPTIMA
WOS研究方向Mathematics ; Science & Technology - Other Topics
引用统计
文献类型期刊论文
条目标识符http://ir.sia.cn/handle/173321/20738
专题数字工厂研究室
通讯作者He MW(何茂伟); Chen HN(陈瀚宁)
作者单位1.Department of Information Service & Intelligent Control, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
2.University of Chinese Academy of Sciences, Beijing 100039, China
3.Shenyang University, Shenyang 110044, China
4.School of Computer Science and Software, Tianjin Polytechnic University, Tianjin 300387, China
推荐引用方式
GB/T 7714
Wang DP,Hu KY,Ma LB,et al. Multispecies Coevolution Particle Swarm Optimization Based on Previous Search History[J]. DISCRETE DYNAMICS IN NATURE AND SOCIETY,2017,2017:1-22.
APA Wang DP,Hu KY,Ma LB,He MW,&Chen HN.(2017).Multispecies Coevolution Particle Swarm Optimization Based on Previous Search History.DISCRETE DYNAMICS IN NATURE AND SOCIETY,2017,1-22.
MLA Wang DP,et al."Multispecies Coevolution Particle Swarm Optimization Based on Previous Search History".DISCRETE DYNAMICS IN NATURE AND SOCIETY 2017(2017):1-22.
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