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	Artificial bee colony algorithm based on k-means clustering for multiobjective optimal power flow problem
	Sun, Liling1,2; Hu, Jingtao1; Chen, Hanning3
刊名	Mathematical problems in engineering
	2015
页码	18
ISSN号	1024-123X
DOI	10.1155/2015/762853
通讯作者	Hu, jingtao(hujingtao@sia.cn)
英文摘要	An improvedmultiobjective abcalgorithmbased on k-means clustering, called cmoabc, is proposed. to fasten the convergence rate of the canonical moabc, the way of information communication in the employed bees' phase is modified. for keeping the population diversity, the multiswarm technology based on k-means clustering is employed to decompose the population into many clusters. due to each subcomponent evolving separately, after every specific iteration, the population will be reclustered to facilitate information exchange among different clusters. application of the new cmoabc on several multiobjective benchmark functions shows a marked improvement in performance over the fast nondominated sorting genetic algorithm (nsga-ii), the multiobjective particle swarm optimizer (mopso), and the multiobjective abc (moabc). finally, the cmoabc is applied to solve the real-world optimal power flow (opf) problem that considers the cost, loss, and emission impacts as the objective functions. the 30-bus ieee test system is presented to illustrate the application of the proposed algorithm. the simulation results demonstrate that, compared to nsga-ii, mopso, and moabc, the proposed cmoabc is superior for solving opf problem, in terms of optimization accuracy.
WOS关键词	BIOGEOGRAPHY-BASED OPTIMIZATION ; EMISSION LOAD DISPATCH ; GENETIC ALGORITHMS ; ABC ALGORITHM ; COST ; STRATEGY ; OPF
WOS研究方向	Engineering ; Mathematics
WOS类目	Engineering, Multidisciplinary ; Mathematics, Interdisciplinary Applications
语种	英语
出版者	HINDAWI PUBLISHING CORPORATION
WOS记录号	WOS:000355822100001
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/2376704
专题	中国科学院大学
通讯作者	Hu, Jingtao
作者单位	1.Chinese Acad Sci, Shenyang Inst Automat, Dept Informat Serv & Intelligent Control, Shenyang 110016, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Tianjin Polytech Univ, Sch Comp Sci & Software, Tianjin 300387, Peoples R China
推荐引用方式 GB/T 7714	Sun, Liling,Hu, Jingtao,Chen, Hanning. Artificial bee colony algorithm based on k-means clustering for multiobjective optimal power flow problem[J]. Mathematical problems in engineering,2015:18.
APA	Sun, Liling,Hu, Jingtao,&Chen, Hanning.(2015).Artificial bee colony algorithm based on k-means clustering for multiobjective optimal power flow problem.Mathematical problems in engineering,18.
MLA	Sun, Liling,et al."Artificial bee colony algorithm based on k-means clustering for multiobjective optimal power flow problem".Mathematical problems in engineering (2015):18.

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