Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/10460
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dc.contributor.authorKöse, S.Y.-
dc.contributor.authorDemir, Leyla-
dc.contributor.authorTunal, S.-
dc.contributor.authorEliiyi, D.T.-
dc.date.accessioned2019-08-16T13:18:51Z
dc.date.available2019-08-16T13:18:51Z
dc.date.issued2015-
dc.identifier.issn0305-215X-
dc.identifier.urihttps://hdl.handle.net/11499/10460-
dc.identifier.urihttps://doi.org/10.1080/0305215X.2013.875166-
dc.description.abstractIn manufacturing systems, optimal buffer allocation has a considerable impact on capacity improvement. This study presents a simulation optimization procedure to solve the buffer allocation problem in a heat exchanger production plant so as to improve the capacity of the system. For optimization, three metaheuristic-based search algorithms, i.e. a binary-genetic algorithm (B-GA), a binary-simulated annealing algorithm (B-SA) and a binary-tabu search algorithm (B-TS), are proposed. These algorithms are integrated with the simulation model of the production line. The simulation model, which captures the stochastic and dynamic nature of the production line, is used as an evaluation function for the proposed metaheuristics. The experimental study with benchmark problem instances from the literature and the real-life problem show that the proposed B-TS algorithm outperforms B-GA and B-SA in terms of solution quality. © 2014 Taylor and Francis.en_US
dc.language.isoenen_US
dc.publisherTaylor and Francis Ltd.en_US
dc.relation.ispartofEngineering Optimizationen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectbuffer allocation problemen_US
dc.subjectgenetic algorithmsen_US
dc.subjectsimulated annealingen_US
dc.subjectsimulation optimizationen_US
dc.subjecttabu searchen_US
dc.subjectAlgorithmsen_US
dc.subjectBenchmarkingen_US
dc.subjectLearning algorithmsen_US
dc.subjectManufactureen_US
dc.subjectOptimizationen_US
dc.subjectSimulated annealingen_US
dc.subjectStochastic modelsen_US
dc.subjectStochastic systemsen_US
dc.subjectTabu searchen_US
dc.subjectBenchmark-problem instancesen_US
dc.subjectBinary genetic algorithmen_US
dc.subjectBuffer allocationen_US
dc.subjectCapacity improvementen_US
dc.subjectOptimal buffer allocationsen_US
dc.subjectSimulated annealing algorithmsen_US
dc.subjectSimulation optimizationen_US
dc.subjectTabu search algorithmsen_US
dc.subjectGenetic algorithmsen_US
dc.titleCapacity improvement using simulation optimization approaches: A case study in the thermotechnology industryen_US
dc.typeArticleen_US
dc.identifier.volume47en_US
dc.identifier.issue2en_US
dc.identifier.startpage149
dc.identifier.startpage149en_US
dc.identifier.endpage164en_US
dc.identifier.doi10.1080/0305215X.2013.875166-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopus2-s2.0-84924272297en_US
dc.identifier.wosWOS:000346295300001en_US
dc.identifier.scopusqualityQ1-
dc.ownerPamukkale University-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.cerifentitytypePublications-
item.openairetypeArticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.languageiso639-1en-
crisitem.author.dept10.09. Industrial Engineering-
Appears in Collections:Mühendislik Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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