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An evolutionary approach for solving the job shop scheduling problem in a service industry

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dc.citedby6
dc.contributor.authorYousefi M.en_US
dc.contributor.authorYousefi M.en_US
dc.contributor.authorHooshyar D.en_US
dc.contributor.authorOliveira J.A.S.en_US
dc.contributor.authorid55247052200en_US
dc.contributor.authorid53985756300en_US
dc.contributor.authorid56572940600en_US
dc.contributor.authorid57205058645en_US
dc.date.accessioned2023-05-29T06:00:46Z
dc.date.available2023-05-29T06:00:46Z
dc.date.issued2015
dc.description.abstractIn this paper, an evolutionary-based approach based on the discrete particle swarm optimization (DPSO) algorithm is developed for finding the optimum schedule of a registration problem in a university. Minimizing the makespan, which is the total length of the schedule, in a real-world case study is considered as the target function. In order to clarify the problem and the proposed solution a small instance discusses then the problem with the real data is solved. Since the selected case study has the characteristics of job shop scheduling problem (JSSP), it is categorized as a NP-hard problem which makes it difficult to be solved by conventional mathematical approaches in relatively short computation time. � 2015 International Journal of Advances in Intelligent Informatics. All rights reserved.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.26555/ijain.v1i1.5
dc.identifier.epage6
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85035747759
dc.identifier.spage1
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85035747759&doi=10.26555%2fijain.v1i1.5&partnerID=40&md5=20f549a771677c8bb9f83d313f9a4bc9
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/22406
dc.identifier.volume1
dc.publisherUniversitas Ahmad Dahlanen_US
dc.relation.ispartofAll Open Access, Gold, Green
dc.sourceScopus
dc.sourcetitleInternational Journal of Advances in Intelligent Informatics
dc.titleAn evolutionary approach for solving the job shop scheduling problem in a service industryen_US
dc.typeArticleen_US
dspace.entity.typePublication
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