Evolutionary algorithms for flowshop sequencing with non unique jobs

Burdett, Robert L. & Kozan, Erhan (2000) Evolutionary algorithms for flowshop sequencing with non unique jobs. International Transactions in Operational Research, 7(4-5), pp. 401-418.

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Sequencing problems are difficult combinatorial problems because of the extremely large search space of possible solutions and the large number of “local” optimum that arise. Unlike other NP-hard combinatorial problems, the search space in general for sequencing problems (under the makespan objective) consist of sequences with objective function values that lie within only a relatively small amount of each other. This means that when a change is made to the sequence, an improvement or non-improvement is not easily recognised. This makes the problem much more difficult to solve. A number of constructive heuristic’s exist that obtain good solutions in a short period of time, however the output of such algorithms is generally a single sequence which may not be feasible or preferred with respect to industry constraints. Other heuristic algorithms such as Simulated Annealing (SA) and Tabu Search (TS) have also been applied and successes have been reported. The performance however is dependent upon a number of finely tuned parameters and the output is again only a single solution. For these reasons, Evolutionary Algorithms may be a suitable solution strategy and for which limited research has been performed. In this research a number of new evolutionary algorithms have been proposed and a number of modifications have been made to several constructive algorithms to cope with non-unique jobs or jobs with multiple demand. A numerical comparison of a number of benchmark problems and real data of a truck assembly line has also been presented.

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ID Code: 10667
Item Type: Journal Article
Refereed: Yes
Additional Information: For more information or for a copy of the item contact the author at r.burdett@qut.edu.au or see the publisher URL above.
Keywords: sequencing, scheduling, meta, heuristics, flowshop
DOI: 10.1111/j.1475-3995.2000.tb00207.x
ISSN: 0969-6016
Subjects: Australian and New Zealand Standard Research Classification > MATHEMATICAL SCIENCES (010000) > APPLIED MATHEMATICS (010200) > Operations Research (010206)
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright 2000 Blackwell Publishing
Copyright Statement: The definitive version is available at www.blackwell-synergy.com
Deposited On: 12 Nov 2007 00:00
Last Modified: 15 Jan 2009 07:53

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