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A particle swarm optimisation for the no-wait flow shop problem with due date constraints.

dc.contributor.authorSamarghandi, Hamed
dc.date.accessioned2018-11-07T16:17:20Z
dc.date.available2018-11-07T16:17:20Z
dc.date.issued2016
dc.description.abstractThis paper considers the no-wait flow shop scheduling problem with due date constraints. In the no-wait flow shop problem, waiting time is not allowed between successive operations of jobs. Moreover, a due date is associated with the completion of each job. The considered objective function is makespan. This problem is proved to be strongly NP-Hard. In this paper, a particle swarm optimisation (PSO) is developed to deal with the problem. Moreover, the effect of some dispatching rules for generating initial solutions are studied. A Taguchi-based design of experience approach has been followed to determine the effect of the different values of the parameters on the performance of the algorithm. To evaluate the performance of the proposed PSO, a large number of benchmark problems are selected from the literature and solved with different due date and penalty settings. Computational results confirm that the proposed PSO is efficient and competitive; the developed framework is able to improve many of the best-known solutions of the test problems available in the literature.en_US
dc.description.versionPeer Revieweden_US
dc.identifier.citationSamarghandi, H., (2015), A particle swarm optimisation for the no-wait flow shop problem with due date constraints. International Journal of Production Research, 53(9): p. 2853-2870. https://doi.org/10.1080/00207543.2015.1007245en_US
dc.identifier.urihttp://hdl.handle.net/10388/11496
dc.language.isoenen_US
dc.publisherInternational Journal of Production Researchen_US
dc.subjectflow shop schedulingen_US
dc.subjectno-waiten_US
dc.subjectdue date constraintsen_US
dc.subjectmakespanen_US
dc.subjectparticle swarm optimizationen_US
dc.titleA particle swarm optimisation for the no-wait flow shop problem with due date constraints.en_US
dc.typeArticleen_US

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