An ensemble discrete differential evolution for the distributed blocking flowshop scheduling with minimizing makespan criterion

doi:10.1016/j.eswa.2020.113678

	An ensemble discrete differential evolution for the distributed blocking flowshop scheduling with minimizing makespan criterion
	Zhao, Fuqing1 ; Zhao, Lexi 1; Wang, Ling 2; Song, Houbin1
	2020-12-01
发表期刊	Expert Systems with Applications
ISSN	09574174
卷号	160
摘要	The distributed blocking flowshop scheduling problem (DBFSP) plays an essential role in the manufacturing industry and has been proven to be as a strongly NP-hard problem. In this paper, an ensemble discrete differential evolution (EDE) algorithm is proposed to solve the blocking flowshop scheduling problem with the minimization of the makespan in the distributed manufacturing environment. In the EDE algorithm, the candidates are represented as discrete job permutations. Two heuristics method and one random strategy are integrated to provide a set of desirable initial solution for the distributed environment. The front delay, blocking time and idle time are considered in these heuristics methods. The mutation, crossover and selection operators are redesigned to assist the EDE algorithm to execute in the discrete domain. Meanwhile, an elitist retain strategy is introduced into the framework of EDE algorithm to balance the exploitation and exploration ability of the EDE algorithm. The parameters of the EDE algorithm are calibrated by the design of experiments (DOE) method. The computational results and comparisons demonstrated the efficiency and effectiveness of the EDE algorithm for the distributed blocking flowshop scheduling problem. © 2020 Elsevier Ltd
关键词	Computational efficiency Design of experiments Heuristic methods Manufacture NP-hard Optimization Scheduling Computational results Discrete differential evolutions Distributed environments Distributed manufacturing Exploitation and explorations Manufacturing industries Minimizing makespan Selection operators
DOI	10.1016/j.eswa.2020.113678
收录类别	EI ; SCIE
语种	英语
WOS研究方向	Computer Science ; Engineering ; Operations Research & Management Science
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Operations Research & Management Science
WOS记录号	WOS:000573459900019
出版者	Elsevier Ltd
EI入藏号	20203008966139
EI主题词	Evolutionary algorithms
EI分类号	537.1 Heat Treatment Processes - 901.3 Engineering Research - 912.2 Management - 921.5 Optimization Techniques
来源库	Compendex
分类代码	537.1 Heat Treatment Processes - 901.3 Engineering Research - 912.2 Management - 921.5 Optimization Techniques
引用统计	被引频次：121[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/115427
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.Tsinghua Univ, Dept Automat, Beijing 10084, 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,Zhao, Lexi,Wang, Ling,et al. An ensemble discrete differential evolution for the distributed blocking flowshop scheduling with minimizing makespan criterion[J]. Expert Systems with Applications,2020,160.
APA	Zhao, Fuqing,Zhao, Lexi,Wang, Ling,&Song, Houbin.(2020).An ensemble discrete differential evolution for the distributed blocking flowshop scheduling with minimizing makespan criterion.Expert Systems with Applications,160.
MLA	Zhao, Fuqing,et al."An ensemble discrete differential evolution for the distributed blocking flowshop scheduling with minimizing makespan criterion".Expert Systems with Applications 160(2020).