Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.13/27380

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Title
Evolutionary algorithms for scheduling a flowshop manufacturing cell with sequence dependent family setups
Author/Creator
França, Paulo M.;  Gupta, Jatinder N. D.;  Mendes, Alexandre S.;  Moscato, Pablo;  Veltink, Klaas 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.
Relation
Computers & Industrial Engineering Vol. 48, Issue 3, p. 491-506
Publisher Link
http://dx.doi.org/10.1016/j.cie.2003.11.004
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/1959.13/27380
Identifier
ISSN:0360-8352
Reviewed
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Subject
"Computers & Industrial Engineering"
 
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