Sequencing Mixed Model Assembly Line Problem to Minimize Line Stoppages Cost by a Modified Simulated Annealing Algorithm Based on Cloud Theory
<p>This research presents a new application of the cloud theory-based simulated annealing algorithm to solve mixed model assembly line sequencing problems where line stoppage cost is expected to be optimized. This objective is highly significant in mixed model assembly line sequencing problems...
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Islamic Azad University, Qazvin Branch
2011-06-01
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doaj-52f456e7a06341c99cb6b932798585d92020-11-24T23:11:11ZengIslamic Azad University, Qazvin BranchJournal of Optimization in Industrial Engineering2251-99042423-39352011-06-01Volume 4891883Sequencing Mixed Model Assembly Line Problem to Minimize Line Stoppages Cost by a Modified Simulated Annealing Algorithm Based on Cloud TheoryZaman Zamami Amlashi0Mostafa Zandieh1MSc, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, IranAssistant Professor, Department of Industrial Management, Management and Accounting, Shahid Beheshti University, Tehran, Iran<p>This research presents a new application of the cloud theory-based simulated annealing algorithm to solve mixed model assembly line sequencing problems where line stoppage cost is expected to be optimized. This objective is highly significant in mixed model assembly line sequencing problems based on just-in-time production system. Moreover, this type of problem is NP-hard and solving this problem through some classical approaches such as total enumeration or exact mathematical procedures such as dynamic programming is computationally prohibitive. Therefore, we proposed the cloud theory-based simulated annealing algorithm (CSA) to address it. Previous researches indicates that evolutionary algorithms especially simulated annealing (SA) is an appropriate method to solve this problem; so we compared CSA with SA in this study to validate the proposed CSA algorithm. Experimentation shows that the CSA approach outperforms the SA approach in both CPU time and objective function especially in large size problems.</p>http://www.qjie.ir/article_83_96ddd4455af4f1acf5518eaebaac91c1.pdfSequencing problemMixed-model assembly lineJust-in-time production systemCloud theorysimulated annealingMinimizing line stoppages |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Zaman Zamami Amlashi Mostafa Zandieh |
spellingShingle |
Zaman Zamami Amlashi Mostafa Zandieh Sequencing Mixed Model Assembly Line Problem to Minimize Line Stoppages Cost by a Modified Simulated Annealing Algorithm Based on Cloud Theory Journal of Optimization in Industrial Engineering Sequencing problem Mixed-model assembly line Just-in-time production system Cloud theory simulated annealing Minimizing line stoppages |
author_facet |
Zaman Zamami Amlashi Mostafa Zandieh |
author_sort |
Zaman Zamami Amlashi |
title |
Sequencing Mixed Model Assembly Line Problem to Minimize Line Stoppages Cost by a Modified Simulated Annealing Algorithm Based on Cloud Theory |
title_short |
Sequencing Mixed Model Assembly Line Problem to Minimize Line Stoppages Cost by a Modified Simulated Annealing Algorithm Based on Cloud Theory |
title_full |
Sequencing Mixed Model Assembly Line Problem to Minimize Line Stoppages Cost by a Modified Simulated Annealing Algorithm Based on Cloud Theory |
title_fullStr |
Sequencing Mixed Model Assembly Line Problem to Minimize Line Stoppages Cost by a Modified Simulated Annealing Algorithm Based on Cloud Theory |
title_full_unstemmed |
Sequencing Mixed Model Assembly Line Problem to Minimize Line Stoppages Cost by a Modified Simulated Annealing Algorithm Based on Cloud Theory |
title_sort |
sequencing mixed model assembly line problem to minimize line stoppages cost by a modified simulated annealing algorithm based on cloud theory |
publisher |
Islamic Azad University, Qazvin Branch |
series |
Journal of Optimization in Industrial Engineering |
issn |
2251-9904 2423-3935 |
publishDate |
2011-06-01 |
description |
<p>This research presents a new application of the cloud theory-based simulated annealing algorithm to solve mixed model assembly line sequencing problems where line stoppage cost is expected to be optimized. This objective is highly significant in mixed model assembly line sequencing problems based on just-in-time production system. Moreover, this type of problem is NP-hard and solving this problem through some classical approaches such as total enumeration or exact mathematical procedures such as dynamic programming is computationally prohibitive. Therefore, we proposed the cloud theory-based simulated annealing algorithm (CSA) to address it. Previous researches indicates that evolutionary algorithms especially simulated annealing (SA) is an appropriate method to solve this problem; so we compared CSA with SA in this study to validate the proposed CSA algorithm. Experimentation shows that the CSA approach outperforms the SA approach in both CPU time and objective function especially in large size problems.</p> |
topic |
Sequencing problem Mixed-model assembly line Just-in-time production system Cloud theory simulated annealing Minimizing line stoppages |
url |
http://www.qjie.ir/article_83_96ddd4455af4f1acf5518eaebaac91c1.pdf |
work_keys_str_mv |
AT zamanzamamiamlashi sequencingmixedmodelassemblylineproblemtominimizelinestoppagescostbyamodifiedsimulatedannealingalgorithmbasedoncloudtheory AT mostafazandieh sequencingmixedmodelassemblylineproblemtominimizelinestoppagescostbyamodifiedsimulatedannealingalgorithmbasedoncloudtheory |
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1725605378780037120 |