标题:Balancing Problem of Stochastic Large-Scale U-Type Assembly Lines Using a Modified Evolutionary Algorithm
作者:Zhang, Honghao; Zhang, Chaoyong; Peng, Yong; Wang, Danqi; Tian, Guangdong; Liu, Xu; Peng, Yuexiang
作者机构:[Zhang, Honghao; Peng, Yong] Cent S Univ, Sch Traff & Transportat Engn, Minist Educ, Key Lab Traff Safety Track, Changsha 410000, Hunan, Peoples R Chi 更多
通讯作者:Peng, Y;Tian, GD;Peng, Yong
通讯作者地址:[Peng, Y]Cent S Univ, Sch Traff & Transportat Engn, Minist Educ, Key Lab Traff Safety Track, Changsha 410000, Hunan, Peoples R China;[Tian, GD]Shandon 更多
来源:IEEE ACCESS
出版年:2018
卷:6
页码:78414-78424
DOI:10.1109/ACCESS.2018.2885030
关键词:U-type assembly line; data analysis; large-scale; stochastic properties;; evolutionary algorithm
摘要:U-type assembly lines have become a mainstream mode in manufacturing because of the higher flexibility and productivity compared with straight lines. Since the balancing problem of a large-scale U-type assembly line is known to be NP-hard, effective mathematical model and evolutionary algorithm are needed to solve this problem. This paper reviews the research status of the related literature in recent years and presents a hybrid evolutionary algorithm, namely, modified ant colony optimization inspired by the process of simulated annealing, to reduce the possibility of being trapped in a local optimum for the balancing problem of stochastic large-scale U-type assembly line. A modified mathematical model for this balancing problem considering stochastic properties is formulated. Furthermore, comparisons with genetic algorithm and imperialist competitive algorithm are conducted to evaluate this proposed method. The results indicate that this proposed algorithm outperforms prior methods in this balancing problem.
收录类别:EI;SCOPUS;SCIE
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85058655405&doi=10.1109%2fACCESS.2018.2885030&partnerID=40&md5=1a3d76e64a897688f1a21eed9dd22b71
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