A Genetic Algorithm for Cellular Manufacturing Design and Layout

Cellular manufacturing (CM) is an approach that can be used to enhance both flexibility and efficiency in today’s small-to-medium lot production environment. The design of a CM system (CMS) often involves three major decisions: cell formation, group layout, and group schedule. Ideally, these decisio...

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Main Authors: WU, Xiaodan, CHU, Chao-Hsien, WANG, Yunfeng, YAN, Weili
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語言:English
出版: Institutional Knowledge at Singapore Management University 2007
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在線閱讀:https://ink.library.smu.edu.sg/sis_research/1763
https://ink.library.smu.edu.sg/context/sis_research/article/2762/viewcontent/1_s2.0_S0377221706004012_pv.pdf
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spelling sg-smu-ink.sis_research-27622023-08-29T07:12:47Z A Genetic Algorithm for Cellular Manufacturing Design and Layout WU, Xiaodan CHU, Chao-Hsien WANG, Yunfeng YAN, Weili Cellular manufacturing (CM) is an approach that can be used to enhance both flexibility and efficiency in today’s small-to-medium lot production environment. The design of a CM system (CMS) often involves three major decisions: cell formation, group layout, and group schedule. Ideally, these decisions should be addressed simultaneously in order to obtain the best results. However, due to the complexity and NP-complete nature of each decision and the limitations of traditional approaches, most researchers have only addressed these decisions sequentially or independently. In this study, a hierarchical genetic algorithm is developed to simultaneously form manufacturing cells and determine the group layout of a CMS. The intrinsic features of our proposed algorithm include a hierarchical chromosome structure to encode two important cell design decisions, a new selection scheme to dynamically consider two correlated fitness functions, and a group mutation operator to increase the probability of mutation. From the computational analyses, these proposed structure and operators are found to be effective in improving solution quality as well as accelerating convergence. 2007-08-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/1763 info:doi/10.1016/j.ejor.2006.05.035 https://ink.library.smu.edu.sg/context/sis_research/article/2762/viewcontent/1_s2.0_S0377221706004012_pv.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Genetic algorithms Cellular manufacturing Cell formation Group layout Numerical Analysis and Scientific Computing Theory and Algorithms
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Genetic algorithms
Cellular manufacturing
Cell formation
Group layout
Numerical Analysis and Scientific Computing
Theory and Algorithms
spellingShingle Genetic algorithms
Cellular manufacturing
Cell formation
Group layout
Numerical Analysis and Scientific Computing
Theory and Algorithms
WU, Xiaodan
CHU, Chao-Hsien
WANG, Yunfeng
YAN, Weili
A Genetic Algorithm for Cellular Manufacturing Design and Layout
description Cellular manufacturing (CM) is an approach that can be used to enhance both flexibility and efficiency in today’s small-to-medium lot production environment. The design of a CM system (CMS) often involves three major decisions: cell formation, group layout, and group schedule. Ideally, these decisions should be addressed simultaneously in order to obtain the best results. However, due to the complexity and NP-complete nature of each decision and the limitations of traditional approaches, most researchers have only addressed these decisions sequentially or independently. In this study, a hierarchical genetic algorithm is developed to simultaneously form manufacturing cells and determine the group layout of a CMS. The intrinsic features of our proposed algorithm include a hierarchical chromosome structure to encode two important cell design decisions, a new selection scheme to dynamically consider two correlated fitness functions, and a group mutation operator to increase the probability of mutation. From the computational analyses, these proposed structure and operators are found to be effective in improving solution quality as well as accelerating convergence.
format text
author WU, Xiaodan
CHU, Chao-Hsien
WANG, Yunfeng
YAN, Weili
author_facet WU, Xiaodan
CHU, Chao-Hsien
WANG, Yunfeng
YAN, Weili
author_sort WU, Xiaodan
title A Genetic Algorithm for Cellular Manufacturing Design and Layout
title_short A Genetic Algorithm for Cellular Manufacturing Design and Layout
title_full A Genetic Algorithm for Cellular Manufacturing Design and Layout
title_fullStr A Genetic Algorithm for Cellular Manufacturing Design and Layout
title_full_unstemmed A Genetic Algorithm for Cellular Manufacturing Design and Layout
title_sort genetic algorithm for cellular manufacturing design and layout
publisher Institutional Knowledge at Singapore Management University
publishDate 2007
url https://ink.library.smu.edu.sg/sis_research/1763
https://ink.library.smu.edu.sg/context/sis_research/article/2762/viewcontent/1_s2.0_S0377221706004012_pv.pdf
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