An Inverse Power Generation Mechanism Based Fruit Fly Algorithm for Function Optimization

doi:10.1007/s11424-018-7250-5

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	An Inverse Power Generation Mechanism Based Fruit Fly Algorithm for Function Optimization
	Liu Ao 1,2,3; Deng Xudong 1,2,3; Ren Liang 1,2,3; Liu Ying 4; Liu Bo5
	2019-04-01
发表期刊	JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY
ISSN	1009-6124
卷号	32 期号:2 页码:634-656
摘要	As a novel population-based optimization algorithm, fruit fly optimization (FFO) algorithm is inspired by the foraging behavior of fruit flies and possesses the advantages of simple search operations and easy implementation. Just like most population-based evolutionary algorithms, the basic FFO also suffers from being trapped in local optima for function optimization due to premature convergence. In this paper, an improved FFO, named IPGS-FFO, is proposed in which two novel strategies are incorporated into the conventional FFO. Specifically, a smell sensitivity parameter together with an inverse power generation mechanism (IPGS) is introduced to enhance local exploitation. Moreover, a dynamic shrinking search radius strategy is incorporated so as to enhance the global exploration over search space by adaptively adjusting the searching area in the problem domain. The statistical performance of FFO, the proposed IPGS-FFO, three state-of-the-art FFO variants, and six metaheuristics are tested on twenty-six well-known unimodal and multimodal benchmark functions with dimension 30, respectively. Experimental results and comparisons show that the proposed IPGS-FFO achieves better performance than three FFO variants and competitive performance against six other meta-heuristics in terms of the solution accuracy and convergence rate.
关键词	Evolutionary algorithms fruit fly optimization function optimization meta-heuristics
DOI	10.1007/s11424-018-7250-5
语种	英语
资助项目	National Natural Science Foundation of China[71701156] ; National Natural Science Foundation of China[71390331] ; National Natural Science Foundation of China[71690242] ; Natural Science Foundation of Hubei Province of China[2017CFB427] ; Key Research Program of Frontier Sciences for Chinese Academy of Sciences[QYZDB-SSW-SYS020] ; Humanity and Social Science Youth Foundation of Ministry of Education of China[16YJCZH056] ; Hubei Province Department of Education Humanities and Social Sciences Research Project[17Q034] ; Open Funding of Center for Service Science and Engineering, Wuhan University of Science and Technology[CSSE2017KA01] ; Open Funding of Intelligent Information Processing and Real-time Industrial System[2016znss18B] ; Young Incubation Program of Wuhan University of Science and Technology[2016xz017] ; Young Incubation Program of Wuhan University of Science and Technology[2017xz031]
WOS研究方向	Mathematics
WOS类目	Mathematics, Interdisciplinary Applications
WOS记录号	WOS:000462987000012
出版者	SPRINGER HEIDELBERG
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/34353
专题	系统科学研究所
通讯作者	Liu Bo
作者单位	1.Wuhan Univ Sci & Technol, Sch Management, Wuhan 430065, Hubei, Peoples R China 2.Wuhan Univ Sci & Technol, Ctr Serv Sci & Engn, Wuhan 430065, Hubei, Peoples R China 3.Hubei Prov Key Lab Intelligent Informat Proc & Re, Wuhan 430065, Hubei, Peoples R China 4.Beihang Univ, Sch Econ & Management, Beijing 100191, Peoples R China 5.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Liu Ao,Deng Xudong,Ren Liang,et al. An Inverse Power Generation Mechanism Based Fruit Fly Algorithm for Function Optimization[J]. JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY,2019,32(2):634-656.
APA	Liu Ao,Deng Xudong,Ren Liang,Liu Ying,&Liu Bo.(2019).An Inverse Power Generation Mechanism Based Fruit Fly Algorithm for Function Optimization.JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY,32(2),634-656.
MLA	Liu Ao,et al."An Inverse Power Generation Mechanism Based Fruit Fly Algorithm for Function Optimization".JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY 32.2(2019):634-656.