Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.13/25140

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Title
Evolutionary algorithms for scheduling a flowshop manufacturing cell with sequence dependent family setups
Author/Creator
Franca, P. M.;  Gupta, J. N. D.;  Mendes, Alexandre;  Moscato, Pablo Alberto;  Veltink, K. J.
Description
This paper considers the problem of scheduling part families and jobs within each part family in a flowshop manufacturing cell with sequence dependent family setups times where it is desired to minimize the makespan while processing parts (jobs) in each family together. Two evolutionary algorithms-a Genetic Algorithm and a Memetic Algorithm with local search-are proposed and empirically evaluated as to their effectiveness in finding optimal permutation schedules. The proposed algorithms use a compact representation for the solution and a hierarchically structured population where the number of possible neighborhoods is limited by dividing the population into clusters. In comparison to a Multi-Start procedure, solutions obtained by the proposed evolutionary algorithms were very close to the lower bounds for all problem instances. Moreover, the comparison against the previous best algorithm, a heuristic named CMD, indicated a considerable performance improvement. (c) 2005 Elsevier Ltd. All rights reserved.
Relation
Computers & Industrial Engineering Vol. 48, no. 3, p. 491-506
Date
2005
Publisher
Pergamon Press
Keyword(s)
flowshop scheduling;  family sequence dependent setups;  manufacturing;  cells;  group technology;  evolutionary algorithms;  empirical results
Resource Type
journal article
Identifier
http://hdl.handle.net/1959.13/25140
Identifier
ISSN:0360-8352
Language
eng
Reviewed
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Subject
"Computers & Industrial Engineering"
 
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