Balancing Problem of Stochastic Large-Scale U-Type Assembly Lines Using a Modified Evolutionary Algorithm
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...
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doaj-334c00a544ed4b95b585cefd168a29ed2021-03-29T21:29:38ZengIEEEIEEE Access2169-35362018-01-016784147842410.1109/ACCESS.2018.28850308573809Balancing Problem of Stochastic Large-Scale U-Type Assembly Lines Using a Modified Evolutionary AlgorithmHonghao Zhang0https://orcid.org/0000-0003-1866-9928Chaoyong Zhang1Yong Peng2https://orcid.org/0000-0003-0101-0342Danqi Wang3Guangdong Tian4https://orcid.org/0000-0001-9794-294XXu Liu5Yuexiang Peng6Key Laboratory of Traffic Safety on Track of Ministry of Education, School of Traffic and Transportation Engineering, Central South University, Changsha, ChinaState Key Laboratory of Digital Manufacturing Equipment & Technology, Huazhong University of Science and Technology, Wuhan, ChinaKey Laboratory of Traffic Safety on Track of Ministry of Education, School of Traffic and Transportation Engineering, Central South University, Changsha, ChinaCollege of Automotive Engineering, Jilin University, Changchun, ChinaSchool of Mechanical Engineering, Shandong University, Jinan, ChinaTransportation College, Jilin University, Changchun, ChinaBusiness and Commerce Department, Hunan Industry Polytechnic, Changsha, ChinaU-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.https://ieeexplore.ieee.org/document/8573809/U-type assembly linedata analysislarge-scalestochastic propertiesevolutionary algorithm |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Honghao Zhang Chaoyong Zhang Yong Peng Danqi Wang Guangdong Tian Xu Liu Yuexiang Peng |
spellingShingle |
Honghao Zhang Chaoyong Zhang Yong Peng Danqi Wang Guangdong Tian Xu Liu Yuexiang Peng Balancing Problem of Stochastic Large-Scale U-Type Assembly Lines Using a Modified Evolutionary Algorithm IEEE Access U-type assembly line data analysis large-scale stochastic properties evolutionary algorithm |
author_facet |
Honghao Zhang Chaoyong Zhang Yong Peng Danqi Wang Guangdong Tian Xu Liu Yuexiang Peng |
author_sort |
Honghao Zhang |
title |
Balancing Problem of Stochastic Large-Scale U-Type Assembly Lines Using a Modified Evolutionary Algorithm |
title_short |
Balancing Problem of Stochastic Large-Scale U-Type Assembly Lines Using a Modified Evolutionary Algorithm |
title_full |
Balancing Problem of Stochastic Large-Scale U-Type Assembly Lines Using a Modified Evolutionary Algorithm |
title_fullStr |
Balancing Problem of Stochastic Large-Scale U-Type Assembly Lines Using a Modified Evolutionary Algorithm |
title_full_unstemmed |
Balancing Problem of Stochastic Large-Scale U-Type Assembly Lines Using a Modified Evolutionary Algorithm |
title_sort |
balancing problem of stochastic large-scale u-type assembly lines using a modified evolutionary algorithm |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2018-01-01 |
description |
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. |
topic |
U-type assembly line data analysis large-scale stochastic properties evolutionary algorithm |
url |
https://ieeexplore.ieee.org/document/8573809/ |
work_keys_str_mv |
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1724192853357232128 |