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dc.contributor.authorShojaeibarjouei, Abolfazl
dc.contributor.authorBarabadi, Abbas
dc.contributor.authorTavakkoli-Moghaddam, Reza
dc.date.accessioned2020-04-02T06:21:44Z
dc.date.available2020-04-02T06:21:44Z
dc.date.issued2019
dc.description.abstractThis paper considers a non-preemptive open shop scheduling problem (OSSP), in which machines are not available to process jobs on known periodic interval times resulted from periodic service repair, rest period, and so on. Asymmetric transportation time between machines is considered, which can be different from one job to another. The objective is to minimize the weighted mean completion time (WMCT). Since the problem is categorized into NP-hard class, two meta-heuristic algorithms including genetic algorithm (GA) and differential evolution (DE) are proposed. Meanwhile, a new initial population is introduced, which significantly improves the performance of the algorithms. Finally, the performance of the algorithms is validated through some large-sized instances and the results are discussed.en_US
dc.identifier.citationShojaeibarjouei A, Barabadi A, Tavakkoli-Moghaddam.(2019) Non-Preemptive Open Shop Scheduling Considering Machine Availability.<i> IEEE International Conference on Industrial Engineering and Engineering Management, 2019</i>, 1280-84en_US
dc.identifier.cristinIDFRIDAID 1742110
dc.identifier.doi10.1109/IEEM44572.2019.8978648
dc.identifier.issn2157-3611
dc.identifier.issn2157-362X
dc.identifier.urihttps://hdl.handle.net/10037/17971
dc.language.isoengen_US
dc.publisherIEEE (Institute of Electrical and Electronical Engineers)en_US
dc.relation.journalIEEE International Conference on Industrial Engineering and Engineering Management
dc.rights.accessRightsopenAccessen_US
dc.rights.holder©2019 IEEEen_US
dc.subjectVDP::Technology: 500::Mechanical engineering: 570en_US
dc.subjectVDP::Teknologi: 500::Maskinfag: 570en_US
dc.titleNon-Preemptive Open Shop Scheduling Considering Machine Availabilityen_US
dc.type.versionacceptedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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