An improved fuzzy C-means algorithm for manufacturing cell formation

Jie Li; Chao Hsien Chu; Yunfeng Wang; Weili Yan

An improved fuzzy C-means algorithm for manufacturing cell formation

Jie Li, Chao Hsien Chu, Yunfeng Wang, Weili Yan

College of Information Sciences and Technology

Research output: Contribution to journal › Conference article › peer-review

4 Scopus citations

Abstract

This paper presents an improved fuzzy C-means algorithm to solve the manufacturing cell formation problems. The proposed algorithm, which integrates the subtractive algorithm (to produce an initial solution), the fuzzy C-means (FCM) algorithm and a solution selecting procedure (to identify the best solution), remedies the major weaknesses of original FCM clustering. We test the performance of the proposed algorithm with 20 data sets from open literature and 60 generated data sets. Our experiments show that the proposed approach performs much better than the original FCM and the solutions are consistent with the best solutions found in references or the control solutions.

Original language	English (US)
Pages (from-to)	1505-1510
Number of pages	6
Journal	IEEE International Conference on Fuzzy Systems
Volume	2
State	Published - Dec 31 2002

All Science Journal Classification (ASJC) codes

Software
Theoretical Computer Science
Artificial Intelligence
Applied Mathematics

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title = "An improved fuzzy C-means algorithm for manufacturing cell formation",

abstract = "This paper presents an improved fuzzy C-means algorithm to solve the manufacturing cell formation problems. The proposed algorithm, which integrates the subtractive algorithm (to produce an initial solution), the fuzzy C-means (FCM) algorithm and a solution selecting procedure (to identify the best solution), remedies the major weaknesses of original FCM clustering. We test the performance of the proposed algorithm with 20 data sets from open literature and 60 generated data sets. Our experiments show that the proposed approach performs much better than the original FCM and the solutions are consistent with the best solutions found in references or the control solutions.",

author = "Jie Li and Chu, {Chao Hsien} and Yunfeng Wang and Weili Yan",

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AU - Yan, Weili

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Y1 - 2002/12/31

N2 - This paper presents an improved fuzzy C-means algorithm to solve the manufacturing cell formation problems. The proposed algorithm, which integrates the subtractive algorithm (to produce an initial solution), the fuzzy C-means (FCM) algorithm and a solution selecting procedure (to identify the best solution), remedies the major weaknesses of original FCM clustering. We test the performance of the proposed algorithm with 20 data sets from open literature and 60 generated data sets. Our experiments show that the proposed approach performs much better than the original FCM and the solutions are consistent with the best solutions found in references or the control solutions.

AB - This paper presents an improved fuzzy C-means algorithm to solve the manufacturing cell formation problems. The proposed algorithm, which integrates the subtractive algorithm (to produce an initial solution), the fuzzy C-means (FCM) algorithm and a solution selecting procedure (to identify the best solution), remedies the major weaknesses of original FCM clustering. We test the performance of the proposed algorithm with 20 data sets from open literature and 60 generated data sets. Our experiments show that the proposed approach performs much better than the original FCM and the solutions are consistent with the best solutions found in references or the control solutions.

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M3 - Conference article

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