A Fuzzy Multi-Objective Linear Programming Model for Manufacturing Cell Formation

Fuzzy mathematical programming (FMP) has been shown not only providing a better and more flexible way of representing the cell formation (CF) problem of cellular manufacturing, but also improving solution quality and computational efficiency. However, FMP cannot meet the demand of real-world applica...

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Main Authors: TSAI, C.C., Chu, Chao-Hsien
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Language:English
Published: Institutional Knowledge at Singapore Management University 2006
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Online Access:https://ink.library.smu.edu.sg/sis_research/221
http://dx.doi.org/10.1007/11903697_48
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spelling sg-smu-ink.sis_research-12202010-09-24T05:42:03Z A Fuzzy Multi-Objective Linear Programming Model for Manufacturing Cell Formation TSAI, C.C. Chu, Chao-Hsien Fuzzy mathematical programming (FMP) has been shown not only providing a better and more flexible way of representing the cell formation (CF) problem of cellular manufacturing, but also improving solution quality and computational efficiency. However, FMP cannot meet the demand of real-world applications because it can only be used to solve small-size problems. In this paper, we propose a heuristic genetic algorithm (HGA) as a viable solution for solving large-scale fuzzy multi-objective CF problems. Heuristic crossover and mutation operators are developed to improve computational efficiency. Our results show that the HGA outperforms the FMP and goal programming (GP) models in terms of clustering results, computational time, and user friendliness. 2006-04-01T08:00:00Z text https://ink.library.smu.edu.sg/sis_research/221 info:doi/10.1007/11903697_48 http://dx.doi.org/10.1007/11903697_48 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Artificial Intelligence and Robotics
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Artificial Intelligence and Robotics
spellingShingle Artificial Intelligence and Robotics
TSAI, C.C.
Chu, Chao-Hsien
A Fuzzy Multi-Objective Linear Programming Model for Manufacturing Cell Formation
description Fuzzy mathematical programming (FMP) has been shown not only providing a better and more flexible way of representing the cell formation (CF) problem of cellular manufacturing, but also improving solution quality and computational efficiency. However, FMP cannot meet the demand of real-world applications because it can only be used to solve small-size problems. In this paper, we propose a heuristic genetic algorithm (HGA) as a viable solution for solving large-scale fuzzy multi-objective CF problems. Heuristic crossover and mutation operators are developed to improve computational efficiency. Our results show that the HGA outperforms the FMP and goal programming (GP) models in terms of clustering results, computational time, and user friendliness.
format text
author TSAI, C.C.
Chu, Chao-Hsien
author_facet TSAI, C.C.
Chu, Chao-Hsien
author_sort TSAI, C.C.
title A Fuzzy Multi-Objective Linear Programming Model for Manufacturing Cell Formation
title_short A Fuzzy Multi-Objective Linear Programming Model for Manufacturing Cell Formation
title_full A Fuzzy Multi-Objective Linear Programming Model for Manufacturing Cell Formation
title_fullStr A Fuzzy Multi-Objective Linear Programming Model for Manufacturing Cell Formation
title_full_unstemmed A Fuzzy Multi-Objective Linear Programming Model for Manufacturing Cell Formation
title_sort fuzzy multi-objective linear programming model for manufacturing cell formation
publisher Institutional Knowledge at Singapore Management University
publishDate 2006
url https://ink.library.smu.edu.sg/sis_research/221
http://dx.doi.org/10.1007/11903697_48
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