Simultaneous Hierarchical Clustering for Cell Formation Problems with Production Information

The purpose of this paper is to advance the similarity coefficient method to solve cell formation (CF) problems in two aspects. Firstly, while numerous similarity coefficients have been proposed to incorporate different production factors in literature, a weighted sum formulation is applied to aggre...

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Main Authors: Yingyu Zhu, Simon Li
Format: Article
Language:English
Published: Hindawi Limited 2018-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2018/2841325
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spelling doaj-a4a660d778624e1e9105e016cf4309032020-11-24T23:10:44ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472018-01-01201810.1155/2018/28413252841325Simultaneous Hierarchical Clustering for Cell Formation Problems with Production InformationYingyu Zhu0Simon Li1Department of Mechanical and Manufacturing Engineering, University of Calgary, Alberta, CanadaDepartment of Mechanical and Manufacturing Engineering, University of Calgary, Alberta, CanadaThe purpose of this paper is to advance the similarity coefficient method to solve cell formation (CF) problems in two aspects. Firstly, while numerous similarity coefficients have been proposed to incorporate different production factors in literature, a weighted sum formulation is applied to aggregate them into a nonbinary matrix to indicate the dependency strength among machines and parts. This practice allows flexible incorporation of multiple production factors in the resolution of CF problems. Secondly, a two-mode similarity coefficient is applied to simultaneously form machine groups and part families based on the classical framework of hierarchical clustering. This practice not only eliminates the sequential process of grouping machines (or parts) first and then assigning parts (or machines), but also improves the quality of solutions. The proposed clustering method has been tested through twelve literature examples. The results demonstrate that the proposed method can at least yield solutions comparable to the solutions obtained by metaheuristics. It can yield better results in some instances, as well.http://dx.doi.org/10.1155/2018/2841325
collection DOAJ
language English
format Article
sources DOAJ
author Yingyu Zhu
Simon Li
spellingShingle Yingyu Zhu
Simon Li
Simultaneous Hierarchical Clustering for Cell Formation Problems with Production Information
Mathematical Problems in Engineering
author_facet Yingyu Zhu
Simon Li
author_sort Yingyu Zhu
title Simultaneous Hierarchical Clustering for Cell Formation Problems with Production Information
title_short Simultaneous Hierarchical Clustering for Cell Formation Problems with Production Information
title_full Simultaneous Hierarchical Clustering for Cell Formation Problems with Production Information
title_fullStr Simultaneous Hierarchical Clustering for Cell Formation Problems with Production Information
title_full_unstemmed Simultaneous Hierarchical Clustering for Cell Formation Problems with Production Information
title_sort simultaneous hierarchical clustering for cell formation problems with production information
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2018-01-01
description The purpose of this paper is to advance the similarity coefficient method to solve cell formation (CF) problems in two aspects. Firstly, while numerous similarity coefficients have been proposed to incorporate different production factors in literature, a weighted sum formulation is applied to aggregate them into a nonbinary matrix to indicate the dependency strength among machines and parts. This practice allows flexible incorporation of multiple production factors in the resolution of CF problems. Secondly, a two-mode similarity coefficient is applied to simultaneously form machine groups and part families based on the classical framework of hierarchical clustering. This practice not only eliminates the sequential process of grouping machines (or parts) first and then assigning parts (or machines), but also improves the quality of solutions. The proposed clustering method has been tested through twelve literature examples. The results demonstrate that the proposed method can at least yield solutions comparable to the solutions obtained by metaheuristics. It can yield better results in some instances, as well.
url http://dx.doi.org/10.1155/2018/2841325
work_keys_str_mv AT yingyuzhu simultaneoushierarchicalclusteringforcellformationproblemswithproductioninformation
AT simonli simultaneoushierarchicalclusteringforcellformationproblemswithproductioninformation
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