- Title
- Evolutionary algorithms for scheduling a flowshop manufacturing cell with sequence dependent family setups
- Creator
- Franca, P. M.; Gupta, J. N. D.; Mendes, Alexandre; Moscato, Pablo Alberto; Veltink, K. J.
- Relation
- Computers & Industrial Engineering Vol. 48, no. 3, p. 491-506
- Publisher
- Pergamon Press
- Resource Type
- journal article
- Date
- 2005
- 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.
- Subject
- flowshop scheduling; family sequence dependent setups; manufacturing; cells; group technology; evolutionary algorithms; empirical results
- Identifier
- http://hdl.handle.net/1959.13/25140
- Identifier
- uon:145
- Identifier
- ISSN:0360-8352
- Language
- eng
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