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A research survey: review of AI solution strategies of job shop scheduling problem

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dc.contributor.authorÇALIŞ USLU, BANU
dc.contributor.authorBULKAN, SEROL
dc.contributor.authorsCalis, Banu; Bulkan, Serol
dc.date.accessioned2022-03-10T15:25:16Z
dc.date.accessioned2026-01-11T18:38:31Z
dc.date.available2022-03-10T15:25:16Z
dc.date.issued2015
dc.description.abstractThis paper focus on artificial intelligence approaches to NP-hard job shop scheduling (JSS) problem. In the literature successful approaches of artificial intelligence techniques such as neural network, genetic algorithm, multi agent systems, simulating annealing, bee colony optimization, ant colony optimization, particle swarm algorithm, etc. are presented as solution approaches to job shop scheduling problem. These studies are surveyed and their successes are listed in this article.
dc.identifier.doi10.1007/s10845-013-0837-8
dc.identifier.eissn1572-8145
dc.identifier.issn0956-5515
dc.identifier.urihttps://hdl.handle.net/11424/220179
dc.identifier.wosWOS:000361486200012
dc.language.isoeng
dc.publisherSPRINGER
dc.relation.ispartofJOURNAL OF INTELLIGENT MANUFACTURING
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectArtificial intelligence
dc.subjectScheduling
dc.subjectMetaheuristic
dc.subjectANT COLONY OPTIMIZATION
dc.subjectGENETIC ALGORITHM
dc.subjectNEURAL-NETWORKS
dc.subjectPARALLEL MACHINES
dc.subjectSEARCH
dc.subjectTARDINESS
dc.subjectHEURISTICS
dc.subjectRESOURCE
dc.subjectDESIGN
dc.titleA research survey: review of AI solution strategies of job shop scheduling problem
dc.typereview
dspace.entity.typePublication
oaire.citation.endPage973
oaire.citation.issue5
oaire.citation.startPage961
oaire.citation.titleJOURNAL OF INTELLIGENT MANUFACTURING
oaire.citation.volume26

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