A Comparison of Three Array-Based Clustering Techniques for Manufacturing Cellular Formation
This paper examines three array-based clustering algorithms—rank order clustering (ROC), direct clustering analysis (DCA), and bond energy analysis (BEA)—for manufacturing cell formation. According to our test, bond energy analysis outperforms the other two methods, regardless of which measure or da...
Saved in:
| Main Authors: | , |
|---|---|
| 格式: | text |
| 語言: | English |
| 出版: |
Institutional Knowledge at Singapore Management University
1990
|
| 主題: | |
| 在線閱讀: | https://ink.library.smu.edu.sg/sis_research/1798 http://dx.doi.org/10.1080/00207549008942802 |
| 標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
| 機構: | Singapore Management University |
| 語言: | English |
| id |
sg-smu-ink.sis_research-2797 |
|---|---|
| record_format |
dspace |
| spelling |
sg-smu-ink.sis_research-27972013-03-15T10:12:03Z A Comparison of Three Array-Based Clustering Techniques for Manufacturing Cellular Formation CHU, Chao-Hsien TSAI, M. This paper examines three array-based clustering algorithms—rank order clustering (ROC), direct clustering analysis (DCA), and bond energy analysis (BEA)—for manufacturing cell formation. According to our test, bond energy analysis outperforms the other two methods, regardless of which measure or data set is used. If exceptional elements exist in the data set, the BEA algorithm also produces better results than the other two methods without any additional processing. The BEA can compete with other more complicated methods that have appeared in the literature. 1990-01-01T08:00:00Z text https://ink.library.smu.edu.sg/sis_research/1798 info:doi/10.1080/00207549008942802 http://dx.doi.org/10.1080/00207549008942802 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Computer Sciences 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 |
Computer Sciences Operations Research, Systems Engineering and Industrial Engineering |
| spellingShingle |
Computer Sciences Operations Research, Systems Engineering and Industrial Engineering CHU, Chao-Hsien TSAI, M. A Comparison of Three Array-Based Clustering Techniques for Manufacturing Cellular Formation |
| description |
This paper examines three array-based clustering algorithms—rank order clustering (ROC), direct clustering analysis (DCA), and bond energy analysis (BEA)—for manufacturing cell formation. According to our test, bond energy analysis outperforms the other two methods, regardless of which measure or data set is used. If exceptional elements exist in the data set, the BEA algorithm also produces better results than the other two methods without any additional processing. The BEA can compete with other more complicated methods that have appeared in the literature. |
| format |
text |
| author |
CHU, Chao-Hsien TSAI, M. |
| author_facet |
CHU, Chao-Hsien TSAI, M. |
| author_sort |
CHU, Chao-Hsien |
| title |
A Comparison of Three Array-Based Clustering Techniques for Manufacturing Cellular Formation |
| title_short |
A Comparison of Three Array-Based Clustering Techniques for Manufacturing Cellular Formation |
| title_full |
A Comparison of Three Array-Based Clustering Techniques for Manufacturing Cellular Formation |
| title_fullStr |
A Comparison of Three Array-Based Clustering Techniques for Manufacturing Cellular Formation |
| title_full_unstemmed |
A Comparison of Three Array-Based Clustering Techniques for Manufacturing Cellular Formation |
| title_sort |
comparison of three array-based clustering techniques for manufacturing cellular formation |
| publisher |
Institutional Knowledge at Singapore Management University |
| publishDate |
1990 |
| url |
https://ink.library.smu.edu.sg/sis_research/1798 http://dx.doi.org/10.1080/00207549008942802 |
| _version_ |
1770571501462880256 |