Enhanced artificial bee colony algorithm through differential evolution

doi:10.1016/j.asoc.2015.10.070

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	Enhanced artificial bee colony algorithm through differential evolution
	Gao, Wei-feng 1; Huang, Ling-ling 1; Wang, Jue 2; Liu, San-yang 3; Qin, Chuan-dong 4,5
	2016-11-01
发表期刊	APPLIED SOFT COMPUTING
ISSN	1568-4946
卷号	48 页码:137-150
摘要	Artificial bee colony algorithm (ABC) is a relatively new optimization algorithm. However, ABC does well in exploration but badly in exploitation. One possible way to improve the exploitation ability of the algorithm is to combine ABC with other operations. Differential evolution (DE) can be considered as a good choice for this purpose. Based on this consideration, we propose a new algorithm, i.e. DGABC, which combines DE with gbest-guided ABC (GABC) by an evaluation strategy with an attempt to utilize more prior information of the previous search experience to speed up the convergence. In addition, to improve the global convergence, when producing the initial population, a chaotic opposition-based population initialization method is employed. The comparison results on a set of 27 benchmark functions demonstrate that the proposed method has better performance than the other algorithms. (C) 2016 Elsevier B.V. All rights reserved.
关键词	Artificial bee colony algorithm Differential evolution Population initialization Evaluation strategy
DOI	10.1016/j.asoc.2015.10.070
语种	英语
资助项目	National Natural Science Foundation of China[61402534] ; National Natural Science Foundation of China[61373174] ; National Natural Science Foundation of China[61562001] ; Shandong Provincial Natural Science Foundation, China[ZR2014FQ002] ; Shandong Provincial Natural Science Foundation, China[ZR2013FQ007] ; Fundamental Research Funds for the Central Universities[14CX02160A] ; Fundamental Research Funds for the Central Universities[15CX02057A]
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence ; Computer Science, Interdisciplinary Applications
WOS记录号	WOS:000389549400011
出版者	ELSEVIER SCIENCE BV
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/24355
专题	中国科学院数学与系统科学研究院
通讯作者	Gao, Wei-feng
作者单位	1.China Univ Petr, Sch Sci, Qingdao 266580, Peoples R China 2.Acad Math & Syst Sci, CAS, Ctr Forecasting Sci, Beijing 100190, Peoples R China 3.Xidian Univ, Sch Math & Stat, Xian 710071, Shannxi, Peoples R China 4.Beifang Univ Nationalities, Math Coll, Yinchuan 750021, Peoples R China 5.Beifang Univ Nationalities, Informat Sci Coll, Yinchuan 750021, Peoples R China
推荐引用方式 GB/T 7714	Gao, Wei-feng,Huang, Ling-ling,Wang, Jue,et al. Enhanced artificial bee colony algorithm through differential evolution[J]. APPLIED SOFT COMPUTING,2016,48:137-150.
APA	Gao, Wei-feng,Huang, Ling-ling,Wang, Jue,Liu, San-yang,&Qin, Chuan-dong.(2016).Enhanced artificial bee colony algorithm through differential evolution.APPLIED SOFT COMPUTING,48,137-150.
MLA	Gao, Wei-feng,et al."Enhanced artificial bee colony algorithm through differential evolution".APPLIED SOFT COMPUTING 48(2016):137-150.