An improved fuzzy C-means algorithm for manufacturing cell formation

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

Research output: Contribution to journalConference article

4 Citations (Scopus)

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 languageEnglish (US)
Pages (from-to)1505-1510
Number of pages6
JournalIEEE International Conference on Fuzzy Systems
Volume2
StatePublished - Dec 31 2002

Fingerprint

Cell Formation
Fuzzy C-means Algorithm
Cellular manufacturing
Manufacturing
Fuzzy C-means Clustering
Fuzzy C-means
Integrate
Experiment

All Science Journal Classification (ASJC) codes

  • Software
  • Theoretical Computer Science
  • Artificial Intelligence
  • Applied Mathematics

Cite this

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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.",
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An improved fuzzy C-means algorithm for manufacturing cell formation. / Li, Jie; Chu, Chao Hsien; Wang, Yunfeng; Yan, Weili.

In: IEEE International Conference on Fuzzy Systems, Vol. 2, 31.12.2002, p. 1505-1510.

Research output: Contribution to journalConference article

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AU - Chu, Chao Hsien

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AU - Yan, Weili

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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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