.png){kind=icon}
返回
Multiple criteria clustering algorithm for solving the group technology problem with multiple process routings
.png){kind=icon}
PRE
AI
DOI：10.1016/S0360-8352(96)00209-4.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This paper considers the machine-part clustering problem in group technology manufacturing in which for a part multiple process routings can be planned. Existing approaches using similarity coefficient to solve the problem suffer from computational burden which arises since;they use the similarity coefficients defined between routings of parts, not machines. Furthermore, existing methods do not deal effectively with the ill-structured problems in which mutually separable cells do not exist. In this paper, we define the generalized machine similarity coefficient. This approach saves considerable computer memory required to store the similarity coefficient information in comparison with the methods using the similarity coefficients defined between parts. Furthermore, the new definition includes existing machine similarity coefficient as a special case. Unlike the existing algorithms using single clustering criterion, a new algorithm using multiple clustering criteria is developed. The algorithm using the generalized machine similarity coefficient effectively solves large-sized and ill-structured problems. Copyright (C) 1997 Elsevier Science Ltd
Keyword:
SIMILARITY COEFFICIENT METHOD
MANUFACTURING SYSTEMS
CELL-FORMATION
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
6.5
论文数:
1.0W
被引数:
3.8W
机构
暂无机构信息
引用论文
.png){kind=icon}
分享收藏分享收藏
查看更多内容