A hybrid algorithm based on self-adaptive gravitational search algorithm and differential evolution

doi:10.1016/j.eswa.2018.07.008

	A hybrid algorithm based on self-adaptive gravitational search algorithm and differential evolution
	Zhao, Fuqing 1; Xue, Feilong 1; Zhang, Yi 2; Ma, Weimin 3; Zhang, Chuck 4; Song, Houbin 1
刊名	EXPERT SYSTEMS WITH APPLICATIONS
	2018-12-15
卷号	113 页码:515-530
关键词	Gravitational search algorithm Differential evolution Self-adaptive mechanism Crossover and mutation operation Exploration and exploitation
ISSN号	0957-4174
DOI	10.1016/j.eswa.2018.07.008
英文摘要	The Gravitational Search Algorithm (GSA) has excellent performance in solving various optimization problems. However, it has been demonstrated that GSA tends to trap into local optima and are easy to lose diversity in the late evolution process. In this paper, a new hybrid algorithm based on self-adaptive Gravitational Search Algorithm (GSA) and Differential Evolution (DE) is proposed for solving single objective optimization, named SGSADE. Firstly, a self-adaptive mechanism based on GSA is proposed for improving the convergence speed and balancing exploration and exploitation. Secondly, the diversity of the population is maintained in the evolution process by using crossover and mutation operation from DE. Besides, to improve the performance of the algorithm, a new perturbation based on Levy flight theory is embedded to enhance exploitation capacity. The simulated results of SGSADE on 2017 CEC benchmark functions show that the SGSADE outperforms the state-of-the-art variant algorithms of the GSA. (C) 2018 Elsevier Ltd. All rights reserved.
资助项目	Science Foundation for Distinguished Youth Scholars of Lanzhou University of Technology[J201405]
WOS研究方向	Computer Science ; Engineering ; Operations Research & Management Science
语种	英语
出版者	PERGAMON-ELSEVIER SCIENCE LTD
WOS记录号	WOS:000446288600033
状态	已发表
内容类型	期刊论文
源URL	[http://119.78.100.223/handle/2XXMBERH/32276]
专题	国际合作处（港澳台办）研究生院
通讯作者	Zhao, Fuqing
作者单位	1.Lanzhou Univ Technol, Sch Comp & Commun Technol, Lanzhou 730050, Gansu, Peoples R China 2.Xijin Univ, Sch Mech Engn, Xian 710123, Shaanxi, Peoples R China 3.Tongji Univ, Sch Econ & Management, Shanghai 200092, Peoples R China 4.Georgia Inst Technol, H Milton Stewart Sch Ind & Syst Engn, Atlanta, GA 30332 USA
推荐引用方式 GB/T 7714	Zhao, Fuqing,Xue, Feilong,Zhang, Yi,et al. A hybrid algorithm based on self-adaptive gravitational search algorithm and differential evolution[J]. EXPERT SYSTEMS WITH APPLICATIONS,2018,113:515-530.
APA	Zhao, Fuqing,Xue, Feilong,Zhang, Yi,Ma, Weimin,Zhang, Chuck,&Song, Houbin.(2018).A hybrid algorithm based on self-adaptive gravitational search algorithm and differential evolution.EXPERT SYSTEMS WITH APPLICATIONS,113,515-530.
MLA	Zhao, Fuqing,et al."A hybrid algorithm based on self-adaptive gravitational search algorithm and differential evolution".EXPERT SYSTEMS WITH APPLICATIONS 113(2018):515-530.