Similarity coefficient methods applied to the cell formation problem: a comparative investigation

Authors:
Yong Yin;Kazuhiko Yasuda
Affiliations:
Industrial and Management Science, Department of Public Policy and Social Studies, Yamagata University, 1-4-12, Kojirakawa-cho, Yamagata-shi 990-8560, Japan;Graduate School of Economics and Management, Tohoku University, Kawauchi, Aoba-ku, Sendai 980-8576, Japan
Venue:
Computers and Industrial Engineering - Special issue: Group technology/cellular manufacturing
Year:
2005

Citing 5
Cited 4

Single linkage versus average linkage clustering in machine cells formation applications

Computers and Industrial Engineering
Clustering algorithms for the design of a cellular manufacturing system—an analysis of their performance

Computers and Industrial Engineering
An efficient algorithm for solving the machine chaining problem in cellular manufacturing

Computers and Industrial Engineering
Cell formation in group technology: review, evaluation and directions for future research

Computers and Industrial Engineering - Cellular manufacturing systems: design, analysis and implementation
A dissimilarity measure for solving the cell formation problem in cellular manufacturing

Computers and Industrial Engineering

Group formation for collaboration in exploratory learning using group technology techniques

KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part II
Two-Stage inter-cell layout design for cellular manufacturing by using ant colony optimization algorithms

ICSI'10 Proceedings of the First international conference on Advances in Swarm Intelligence - Volume Part I
User behaviour-driven group formation through case-based reasoning and clustering

Expert Systems with Applications: An International Journal
An Empirical Evaluation of Similarity Coefficients for Binary Valued Data

International Journal of Data Warehousing and Mining

Quantified Score

Hi-index	0.00

Visualization

Abstract

Although many similarity coefficients have been proposed, very few comparative studies have been done to evaluate the performance of various similarity coefficients. In this paper, we compare the performance of 20 well-known similarity coefficients. Two hundred and fourteen numerical cell formation problems, which are selected from the literature or generated deliberately, are used for the comparative study. Nine performance measures are used for evaluating the goodness of cell formation solutions. Two characteristics, discriminability and stability of the similarity coefficients are tested under different data conditions. From the results, three similarity coefficients are found to be more discriminable. Jaccard is found to be the most stable similarity coefficient. Four similarity coefficients are not recommendable due to their poor performances.