Soft computing in optimizing assembly lines balancing

As part of manufacturing systems, the assembly line has become one of the most valuable researches to accomplish the real world problems related to them. Many efforts have been made to seek the best techniques in optimizing assembly lines. Problem statement: Since it was published by Salveson in 195...

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Main Authors: Matondang, Muhammad Zaini, Jambak, Muhammad Ikhwan
格式: Article
语言:English
出版: Science Publications 2010
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在线阅读:http://eprints.utm.my/id/eprint/26666/1/MuhammadZainiMatondang2010_SoftComputinginOptimizingAssemblyLinesBalancing.pdf
http://eprints.utm.my/id/eprint/26666/
http://dx.doi.org/10.3844/jcssp.2010.141.162
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spelling my.utm.266662019-05-22T01:17:16Z http://eprints.utm.my/id/eprint/26666/ Soft computing in optimizing assembly lines balancing Matondang, Muhammad Zaini Jambak, Muhammad Ikhwan QA75 Electronic computers. Computer science As part of manufacturing systems, the assembly line has become one of the most valuable researches to accomplish the real world problems related to them. Many efforts have been made to seek the best techniques in optimizing assembly lines. Problem statement: Since it was published by Salveson in 1955, some methods and techniques have been developed based on mathematical modeling. In recent years, some researches in Assembly Line Balancing (ALB) have been conducted using Soft Computing (SC) approaches. However, there is no comprehensive survey studies conducted regarding the use of SC in ALB problems, which is became the aim of this study. Approach: This study reviewed published literatures and previous related works that applied SC in solving ALB problems. Main outcomes: This study looks into the suitability of SC approaches in several types of ALB problems. Furthermore, this study provides the classification of ALB problems that can facilitate distinguishing those problems as fields of research. Result: This study found that Genetic Algorithms (GAs) are predominantly applied to solve ALB problems compared to other SC approaches. This high suitability in ALB refers to GAs’ main characteristics that include its robustness and flexibility. These SC approaches have mostly been applied to simple ALB problems, which are not problems that are covered in a real complex manufacturing environment. Conclusion/Recommendations: This study recommends that future researches in ALB should be conducted with regard to other issues, beyond the simple ALB problems and more practical to the industries. Besides the advantages of GAs, there are still opportunities to use other SC approaches and the hybrid-systems among them that could increase the suitability of these approaches, especially for multi-objective ALB problems. This study also recommends that human involvement in ALB needs to be considered as a problem factor in ALB. Science Publications 2010 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/26666/1/MuhammadZainiMatondang2010_SoftComputinginOptimizingAssemblyLinesBalancing.pdf Matondang, Muhammad Zaini and Jambak, Muhammad Ikhwan (2010) Soft computing in optimizing assembly lines balancing. Journal of Computer Science, 6 (2). pp. 141-162. ISSN 1549-3636 http://dx.doi.org/10.3844/jcssp.2010.141.162 DOI:10.3844/jcssp.2010.141.162
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Matondang, Muhammad Zaini
Jambak, Muhammad Ikhwan
Soft computing in optimizing assembly lines balancing
description As part of manufacturing systems, the assembly line has become one of the most valuable researches to accomplish the real world problems related to them. Many efforts have been made to seek the best techniques in optimizing assembly lines. Problem statement: Since it was published by Salveson in 1955, some methods and techniques have been developed based on mathematical modeling. In recent years, some researches in Assembly Line Balancing (ALB) have been conducted using Soft Computing (SC) approaches. However, there is no comprehensive survey studies conducted regarding the use of SC in ALB problems, which is became the aim of this study. Approach: This study reviewed published literatures and previous related works that applied SC in solving ALB problems. Main outcomes: This study looks into the suitability of SC approaches in several types of ALB problems. Furthermore, this study provides the classification of ALB problems that can facilitate distinguishing those problems as fields of research. Result: This study found that Genetic Algorithms (GAs) are predominantly applied to solve ALB problems compared to other SC approaches. This high suitability in ALB refers to GAs’ main characteristics that include its robustness and flexibility. These SC approaches have mostly been applied to simple ALB problems, which are not problems that are covered in a real complex manufacturing environment. Conclusion/Recommendations: This study recommends that future researches in ALB should be conducted with regard to other issues, beyond the simple ALB problems and more practical to the industries. Besides the advantages of GAs, there are still opportunities to use other SC approaches and the hybrid-systems among them that could increase the suitability of these approaches, especially for multi-objective ALB problems. This study also recommends that human involvement in ALB needs to be considered as a problem factor in ALB.
format Article
author Matondang, Muhammad Zaini
Jambak, Muhammad Ikhwan
author_facet Matondang, Muhammad Zaini
Jambak, Muhammad Ikhwan
author_sort Matondang, Muhammad Zaini
title Soft computing in optimizing assembly lines balancing
title_short Soft computing in optimizing assembly lines balancing
title_full Soft computing in optimizing assembly lines balancing
title_fullStr Soft computing in optimizing assembly lines balancing
title_full_unstemmed Soft computing in optimizing assembly lines balancing
title_sort soft computing in optimizing assembly lines balancing
publisher Science Publications
publishDate 2010
url http://eprints.utm.my/id/eprint/26666/1/MuhammadZainiMatondang2010_SoftComputinginOptimizingAssemblyLinesBalancing.pdf
http://eprints.utm.my/id/eprint/26666/
http://dx.doi.org/10.3844/jcssp.2010.141.162
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