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A hybrid genetic algorithm for manufacturing cell formation

José F. Gonçalves (jfgoncal***at***fe.up.pt)
Mauricio G. C. Resende (mgcr***at***research.att.com)

Abstract: Cellular manufacturing emerged as a production strategy capable of solving the problems of complexity and long manufacturing lead times in batch production. The fundamental problem in cellular manufacturing is the formation of product families and machine cells. This paper presents a new approach for obtaining machine cells and product families. The approach combines a local search heuristic with a genetic algorithm. Computational experience with the algorithm on a set of group technology problems available in the literature is also presented. The approach produced solutions with a grouping efficacy that is at least as good as any results previously reported in literature and improved the grouping efficacy for 59 % of the problems.

Keywords: Cellular Manufacturing; Group Technology; Genetic Algorithms; Random Keys

Category 1: Applications -- OR and Management Sciences (Production and Logistics )

Category 2: Combinatorial Optimization (Meta Heuristics )

Citation: AT&T Labs Research Technical Report TD-5FE6RN, AT&T Labs Research, Florham Park, NJ 07932 USA, October 29, 2002.

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Entry Submitted: 10/29/2002
Entry Accepted: 10/29/2002
Entry Last Modified: 06/25/2004

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