A hybrid biogeography-based optimization with variable neighborhood search mechanism for no-wait flow shop scheduling problem

doi:10.1016/j.eswa.2019.02.023

	A hybrid biogeography-based optimization with variable neighborhood search mechanism for no-wait flow shop scheduling problem
	Zhao, Fuqing 3; Qin, Shuo 3; Zhang, Yi 4; Ma, Weimin 2; Zhang, Chuck 1; Song, Houbin 3
刊名	EXPERT SYSTEMS WITH APPLICATIONS
	2019-07-15
卷号	126 页码:321-339
关键词	Biogeography-based optimization No-wait flow shop scheduling problem Block neighborhood structure Markov model Path relink technique
ISSN号	0957-4174
DOI	10.1016/j.eswa.2019.02.023
英文摘要	The no-wait flow shop scheduling problem (NWFSP) plays an essential role in the manufacturing industry. Inspired by the overall process of biogeography theory, the standard biogeography-based optimization (BBO) was constructed with migration and mutation operators. In this paper, a hybrid biogeography-based optimization with variable neighborhood search (HBV) is implemented for solving the NWFSP with the makespan criterion. The modified NEH and the nearest neighbor mechanism are employed to generate a potential initial population. A hybrid migration operator, which combines the path relink technique and the block-based self-improvement strategy, is designed to accelerate the convergence speed of HBV. The iterated greedy (IG) algorithm is introduced into the mutation operator to obtain a promising solution in exploitation phase. A variable neighbor search strategy, which is based on the block neighborhood structure and the insert neighborhood structure, is designed to perform the local search around the current best solution in each generation. Furthermore, the global convergence performance of the HBV is analyzed with the Markov model. The computational results and comparisons with other state-of-art algorithms based on Taillard and VRF benchmark show that the efficiency and performance of HBV for solving NWFSP. (C) 2019 Elsevier Ltd. All rights reserved.
资助项目	Wenzhou Public Welfare Science and Technology project[G20170016]
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:000464486100025
状态	已发表
内容类型	期刊论文
源URL	[http://119.78.100.223/handle/2XXMBERH/31724]
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.Georgia Inst Technol, H Milton Stewart Sch Ind & Syst Engn, Atlanta, GA 30332 USA 2.Tongji Univ, Sch Econ & Management, Shanghai 200092, Peoples R China 3.Lanzhou Univ Technol, Sch Comp & Commun Technol, Lanzhou 730050, Gansu, Peoples R China 4.Xijin Univ, Sch Mech Engn, Xian 710123, Shaanxi, Peoples R China
推荐引用方式 GB/T 7714	Zhao, Fuqing,Qin, Shuo,Zhang, Yi,et al. A hybrid biogeography-based optimization with variable neighborhood search mechanism for no-wait flow shop scheduling problem[J]. EXPERT SYSTEMS WITH APPLICATIONS,2019,126:321-339.
APA	Zhao, Fuqing,Qin, Shuo,Zhang, Yi,Ma, Weimin,Zhang, Chuck,&Song, Houbin.(2019).A hybrid biogeography-based optimization with variable neighborhood search mechanism for no-wait flow shop scheduling problem.EXPERT SYSTEMS WITH APPLICATIONS,126,321-339.
MLA	Zhao, Fuqing,et al."A hybrid biogeography-based optimization with variable neighborhood search mechanism for no-wait flow shop scheduling problem".EXPERT SYSTEMS WITH APPLICATIONS 126(2019):321-339.