A hybrid self-adaptive invasive weed algorithm with differential evolution

doi:10.1080/09540091.2021.1917517

	A hybrid self-adaptive invasive weed algorithm with differential evolution
	Zhao, Fuqing1 ; Du, Songlin 1; Lu, Hao 1; Ma, Weimin 2; Song, Houbin1
	2021-10-02
发表期刊	CONNECTION SCIENCE
ISSN	0954-0091
卷号	33 期号:4 页码:929-953
摘要	The invasive weed algorithm (IWO) is a meta-heuristic algorithm, which is an effective and promising optimiser to address the optimisation problems. In this study, a hybrid algorithm based on the self-adaptive invasive weed algorithm (IWO) and differential evolution algorithm (DE), named SIWODE, is proposed to address the continuous optimisation problems. In the proposed SIWODE, first, the two parameters are adaptively proposed to improve the convergence speed of the algorithm. Second, the crossover and mutation operations are introduced in SIWODE to improve the population diversity and increase the exploration capability during the iterative process. Furthermore, a local perturbation strategy is presented to improve exploitation ability during the late process. The exploration and exploitation ability of the algorithm is effectively balanced by cooperative mechanisms. The experiment results of SIWODE show that the SIWODE has the superior searching quality and stability than other mentioned approaches.
关键词	Continuous optimisation problems invasive weed algorithm differential evolution self-adaptive mechanism local perturbation strategy
DOI	10.1080/09540091.2021.1917517
收录类别	SCIE ; SCOPUS ; EI
语种	英语
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence ; Computer Science, Theory & Methods
WOS记录号	WOS:000643876300001
出版者	TAYLOR & FRANCIS LTD
EI入藏号	20211810275436
EI分类号	723.1 Computer Programming - 921.5 Optimization Techniques - 921.6 Numerical Methods
来源库	WOS
引用统计	被引频次：6[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	https://ir.lut.edu.cn/handle/2XXMBERH/148243
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, Peoples R China; 2.Tongji Univ, Sch Econ & Management, Shanghai, Peoples R China
第一作者单位	兰州理工大学
通讯作者单位	兰州理工大学
第一作者的第一单位	兰州理工大学
推荐引用方式 GB/T 7714	Zhao, Fuqing,Du, Songlin,Lu, Hao,et al. A hybrid self-adaptive invasive weed algorithm with differential evolution[J]. CONNECTION SCIENCE,2021,33(4):929-953.
APA	Zhao, Fuqing,Du, Songlin,Lu, Hao,Ma, Weimin,&Song, Houbin.(2021).A hybrid self-adaptive invasive weed algorithm with differential evolution.CONNECTION SCIENCE,33(4),929-953.
MLA	Zhao, Fuqing,et al."A hybrid self-adaptive invasive weed algorithm with differential evolution".CONNECTION SCIENCE 33.4(2021):929-953.