Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2

group technology Related Abstracts

2 Enhanced Imperialist Competitive Algorithm for the Cell Formation Problem Using Sequence Data

Authors: G. M. Komaki, E. Teymourian, S. Sheikh, S. H. Borghei, M. Mobin

Abstract:

Imperialist competitive algorithm (ICA) is a recent meta-heuristic method that is inspired by the social evolutions for solving NP-Hard problems. The ICA is a population based algorithm which has achieved a great performance in comparison to other meta-heuristics. This study is about developing enhanced ICA approach to solve the cell formation problem (CFP) using sequence data. In addition to the conventional ICA, an enhanced version of ICA, namely EICA, applies local search techniques to add more intensification aptitude and embed the features of exploration and intensification more successfully. Suitable performance measures are used to compare the proposed algorithms with some other powerful solution approaches in the literature. In the same way, for checking the proficiency of algorithms, forty test problems are presented. Five benchmark problems have sequence data, and other ones are based on 0-1 matrices modified to sequence based problems. Computational results elucidate the efficiency of the EICA in solving CFP problems.

Keywords: Sequence Data, imperialist competitive algorithm, cell formation problem, group technology

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1 Spectral Clustering for Manufacturing Cell Formation

Authors: Miin-Shen Yang, Yessica Nataliani

Abstract:

Cell formation (CF) is an important step in group technology. It is used in designing cellular manufacturing systems using similarities between parts in relation to machines so that it can identify part families and machine groups. There are many CF methods in the literature, but there is less spectral clustering used in CF. In this paper, we propose a spectral clustering algorithm for machine-part CF. Some experimental examples are used to illustrate its efficiency. Overall, the spectral clustering algorithm can be used in CF with a wide variety of machine/part matrices.

Keywords: Spectral Clustering, group technology, cell formation, grouping efficiency

Procedia PDF Downloads 208