An improved fuzzy clustering method for cellular manufacturing

J. LI; C.-H. CHU; Y. WANG; W. YAN

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An improved fuzzy clustering method for cellular manufacturing

机译：一种改进的蜂窝制造模糊聚类方法

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Fuzzy c-means (FCM) has been successfully adapted to solve the manufacturing cell formation problem. However, when the problem becomes larger and especially if the data is ill structured, the FCM may result in clustering errors, infeasible solutions, and uneven distribution of parts/machines. In this paper, an improved fuzzy clustering algorithm is proposed to overcome the deficiencies of FCM. We tested the effects of algorithm parameters and compared its performance with the original and two popular FCM modifications. Our study shows that the proposed approach outperformed other alternatives. Most of the solutions it obtained are close to and in some cases better than the control solutions.

机译：模糊c均值（FCM）已成功适用于解决制造单元形成问题。但是，当问题变得更大时，尤其是如果数据结构不良时，FCM可能会导致聚类错误，不可行的解决方案以及零件/机器的不均匀分布。本文提出了一种改进的模糊聚类算法，克服了FCM的不足。我们测试了算法参数的效果，并将其性能与原始和两种流行的FCM修改进行了比较。我们的研究表明，提出的方法优于其他方法。它获得的大多数解决方案都接近于控制解决方案，并且在某些情况下还优于控制解决方案。

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来源
《International Journal of Production Research》 |2007年第5期|p.1049-1062|共14页
作者
J. LI; C.-H. CHU; Y. WANG; W. YAN;
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作者单位

School of Management, Hebei University of Technology, Tianjin 300130 People's Republic of China;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种 eng
中图分类管理学;
关键词
cellular manufacturing; cell formation; fuzzy clustering; fuzzy c-means;

机译：细胞制造;细胞形成;模糊聚类;模糊c均值;

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An improved fuzzy clustering method for cellular manufacturing

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