A self-adaptive harmony PSO search algorithm and its performance analysis

doi:10.1016/j.eswa.2015.05.035

	A self-adaptive harmony PSO search algorithm and its performance analysis
	Zhao, Fuqing 2,3; Liu, Yang 2; Zhang, Chuck 1; Wang, Junbiao 3
刊名	EXPERT SYSTEMS WITH APPLICATIONS
	2015-11-30
卷号	42 期号:21 页码:7436-7455
关键词	Harmony Search algorithm PSO algorithm Self-adaptive scheme Mutation strategy Markov model
ISSN号	0957-4174
DOI	10.1016/j.eswa.2015.05.035
英文摘要	Harmony Search (HS) algorithm is a new population-based meta-heuristic which imitates the music improvisation process and has been successfully applied to a variety of combination optimization problems. In this paper, a self-adaptive harmony particle swarm optimization search algorithm, named SHPSOS, is proposed to solve global continuous optimization problems. Firstly, an efficient initialization scheme based on the PSO algorithm is presented for improving the solution quality of the initial harmony memory (HM). Secondly, a new self-adaptive adjusting scheme for pitch adjusting rate (PAR) and distance bandwidth (BW), which can balance fast convergence and large diversity during the improvisation step, are designed. PAR is dynamically adapted by symmetrical sigmoid curve, and BW is dynamically adjusted by the median of the harmony vector at each generation. Meanwhile, a new effective improvisation scheme based on differential evolution and the best harmony (best individual) is developed to accelerate convergence performance and to improve solution accuracy. Besides, Gaussian mutation strategy is presented and embedded in the SHPSOS algorithm to reinforce the robustness and avoid premature convergence in the evolution process of candidates. Finally, the global convergence performance of the SHPSOS is analyzed with the Markov model to testify the stability of algorithm. Experimental results on thirty-two standard benchmark functions demonstrate that SHPSOS outperforms original HS and the other related algorithms in terms of the solution quality and the stability. (C) 2015 Elsevier Ltd. All rights reserved.
资助项目	Science Foundation for Distinguished Youth Scholars of Lanzhou University of Technology, Lanzhou Science Bureau[2012M521802] ; Science Foundation for Distinguished Youth Scholars of Lanzhou University of Technology, Lanzhou Science Bureau[2013T60889] ; Science Foundation for Distinguished Youth Scholars of Lanzhou University of Technology, Lanzhou Science Bureau[J201405] ; Science Foundation for Distinguished Youth Scholars of Lanzhou University of Technology, Lanzhou Science Bureau[2013-4-64]
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:000360772500015
状态	已发表
内容类型	期刊论文
源URL	[http://119.78.100.223/handle/2XXMBERH/33924]
专题	国际合作处（港澳台办）
通讯作者	Zhao, Fuqing
作者单位	1.Georgia Inst Technol, H Milton Stewart Sch Ind & Syst Engn, Atlanta, GA 30332 USA 2.Lanzhou Univ Technol, Sch Comp & Commun Technol, Lanzhou 730050, Peoples R China 3.Northwestern Polytech Univ, Minist Educ, Key Lab Contemporary Design & Integrated Mfg Tech, Xian 710072, Peoples R China
推荐引用方式 GB/T 7714	Zhao, Fuqing,Liu, Yang,Zhang, Chuck,et al. A self-adaptive harmony PSO search algorithm and its performance analysis[J]. EXPERT SYSTEMS WITH APPLICATIONS,2015,42(21):7436-7455.
APA	Zhao, Fuqing,Liu, Yang,Zhang, Chuck,&Wang, Junbiao.(2015).A self-adaptive harmony PSO search algorithm and its performance analysis.EXPERT SYSTEMS WITH APPLICATIONS,42(21),7436-7455.
MLA	Zhao, Fuqing,et al."A self-adaptive harmony PSO search algorithm and its performance analysis".EXPERT SYSTEMS WITH APPLICATIONS 42.21(2015):7436-7455.