Genetic Algorithmsfor Integrating Cell Formation with Machine Layout and Scheduling

Cellular manufacturing (CM) has been recognized as an innovative practice for companies to gain efficiency as well as flexibility under today’s small-to-medium lot and customization-oriented manufacturing environment. Among the necessary decisions for a successful CM implementation, cell formation (...

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Main Authors: WU, Xiaodan, CHU, Chao-Hsien, WANG, Yunfeng, YUE, Dianmin
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Language:English
Published: Institutional Knowledge at Singapore Management University 2007
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Online Access:https://ink.library.smu.edu.sg/sis_research/1787
http://dx.doi.org/10.1016/j.cie.2007.06.021
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spelling sg-smu-ink.sis_research-27862013-03-15T10:12:03Z Genetic Algorithmsfor Integrating Cell Formation with Machine Layout and Scheduling WU, Xiaodan CHU, Chao-Hsien WANG, Yunfeng YUE, Dianmin Cellular manufacturing (CM) has been recognized as an innovative practice for companies to gain efficiency as well as flexibility under today’s small-to-medium lot and customization-oriented manufacturing environment. Among the necessary decisions for a successful CM implementation, cell formation (CF), group layout (GL) and group scheduling (GS) are the three most popular ones. These decisions are interrelated and may impact each other but they are often treated separately or as a sequential decision in prior research. In this paper, we propose a new approach to concurrently make the CF, GL and GS decisions. A conceptual framework and mathematical model, which integrates these decisions, are proposed. A hierarchical genetic algorithm (HGA) is developed to solve the integrated cell design problem. Two heuristic operators are proposed to enhance its computational performance. The results from our study indicate that: (1) the concurrent approach often found better solutions than the sequential one, and (2) with the proposed heuristic operators, the HGA procedure performed better than without them. 2007-09-01T07:00:00Z text https://ink.library.smu.edu.sg/sis_research/1787 info:doi/10.1016/j.cie.2007.06.021 http://dx.doi.org/10.1016/j.cie.2007.06.021 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Cell formation Group layout Group scheduling Genetic algorithms Cellular manufacturing Computer Sciences Management Information Systems Operations Research, Systems Engineering and Industrial Engineering
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Cell formation
Group layout
Group scheduling
Genetic algorithms
Cellular manufacturing
Computer Sciences
Management Information Systems
Operations Research, Systems Engineering and Industrial Engineering
spellingShingle Cell formation
Group layout
Group scheduling
Genetic algorithms
Cellular manufacturing
Computer Sciences
Management Information Systems
Operations Research, Systems Engineering and Industrial Engineering
WU, Xiaodan
CHU, Chao-Hsien
WANG, Yunfeng
YUE, Dianmin
Genetic Algorithmsfor Integrating Cell Formation with Machine Layout and Scheduling
description Cellular manufacturing (CM) has been recognized as an innovative practice for companies to gain efficiency as well as flexibility under today’s small-to-medium lot and customization-oriented manufacturing environment. Among the necessary decisions for a successful CM implementation, cell formation (CF), group layout (GL) and group scheduling (GS) are the three most popular ones. These decisions are interrelated and may impact each other but they are often treated separately or as a sequential decision in prior research. In this paper, we propose a new approach to concurrently make the CF, GL and GS decisions. A conceptual framework and mathematical model, which integrates these decisions, are proposed. A hierarchical genetic algorithm (HGA) is developed to solve the integrated cell design problem. Two heuristic operators are proposed to enhance its computational performance. The results from our study indicate that: (1) the concurrent approach often found better solutions than the sequential one, and (2) with the proposed heuristic operators, the HGA procedure performed better than without them.
format text
author WU, Xiaodan
CHU, Chao-Hsien
WANG, Yunfeng
YUE, Dianmin
author_facet WU, Xiaodan
CHU, Chao-Hsien
WANG, Yunfeng
YUE, Dianmin
author_sort WU, Xiaodan
title Genetic Algorithmsfor Integrating Cell Formation with Machine Layout and Scheduling
title_short Genetic Algorithmsfor Integrating Cell Formation with Machine Layout and Scheduling
title_full Genetic Algorithmsfor Integrating Cell Formation with Machine Layout and Scheduling
title_fullStr Genetic Algorithmsfor Integrating Cell Formation with Machine Layout and Scheduling
title_full_unstemmed Genetic Algorithmsfor Integrating Cell Formation with Machine Layout and Scheduling
title_sort genetic algorithmsfor integrating cell formation with machine layout and scheduling
publisher Institutional Knowledge at Singapore Management University
publishDate 2007
url https://ink.library.smu.edu.sg/sis_research/1787
http://dx.doi.org/10.1016/j.cie.2007.06.021
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