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An effective Sorensen‐single linkage clustering hybrid algorithm for cell formation problems in cellular manufacturing industry
Author(s) -
S Sathish,
AR Lakshmanan,
P Karuppuswamy,
C Bhagyanathan
Publication year - 2019
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.5211
Subject(s) - cluster analysis , linkage (software) , computation , algorithm , similarity (geometry) , cellular manufacturing , computer science , data mining , mathematics , artificial intelligence , mathematical optimization , biology , biochemistry , image (mathematics) , gene
Summary The paper presented here entails technique that is based upon Sorensen's similarity coefficient as well as the Sorensen‐ Single Linkage Clustering (SLC) algorithm, which essentially is a hybrid clustering approach that has been deployed here to show issue related to cell formation during the process of cellular engineering. In the following paper and study that has been presented here, the suggested hybrid algorithm comparison has been drawn versus the existing clustering algorithms and their performances have been compared specifically the MOD‐SLC modified single linkage or SLC also known as the single linkage clustering algorithm. The Sorensen‐SLC technique and the inferences drawn on the same show that it performs comparatively better when compared with the MOD‐SLC and SLC algorithms. Additionally, the computation that is necessary for this hybrid algorithm is absolutely a bare minimal and the computation processing is effective and easy.