Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13091/534
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dc.contributor.authorBaysal, M. Emin-
dc.contributor.authorSarucan, A.-
dc.contributor.authorBüyüközkan, K.-
dc.contributor.authorEngin, O.-
dc.date.accessioned2021-12-13T10:26:53Z-
dc.date.available2021-12-13T10:26:53Z-
dc.date.issued2021-
dc.identifier.isbn9783030511555-
dc.identifier.issn2194-5357-
dc.identifier.urihttps://doi.org/10.1007/978-3-030-51156-2_167-
dc.identifier.urihttps://hdl.handle.net/20.500.13091/534-
dc.descriptionInternational Conference on Intelligent and Fuzzy Systems, INFUS 2020 -- 21 July 2020 through 23 July 2020 -- -- 242349en_US
dc.description.abstractThe distributed permutation flow shop scheduling problem is a subclass of the permutation flow shop scheduling problem. Distributed scheduling adopts multi-factory with permutation flow shop scheduling environment. At the distributed permutation flow shop scheduling, due to the human factors, the processing times of the jobs on the machines are not known exactly. Thus, in this study, the processing time of the jobs on machines are considered as a triangular fuzzy number. Also, the due dates of the jobs are considered as trapezoidal fuzzy numbers at this research. To solve the distributed fuzzy permutation flow shop scheduling problem with multi-objective an artificial bee colony algorithm is proposed. To the best of our knowledge, this is the first study to solve the distributed fuzzy permutation flow shop scheduling with an artificial bee colony algorithm. The proposed artificial bee colony algorithm is first calibrated on the distributed permutation flow shop scheduling problem. The results showed that the proposed artificial bee colony algorithm is an efficient solution technique for solving distributed fuzzy permutation flow shop scheduling problems. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.en_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofAdvances in Intelligent Systems and Computingen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectArtificial bee colony algorithmen_US
dc.subjectFuzzy distributed permutation flow shopen_US
dc.titleDistributed Fuzzy Permutation Flow Shop Scheduling Problem: A Bee Colony Algorithmen_US
dc.typeConference Objecten_US
dc.identifier.doi10.1007/978-3-030-51156-2_167-
dc.identifier.scopus2-s2.0-85088748877en_US
dc.departmentFakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Endüstri Mühendisliği Bölümüen_US
dc.identifier.volume1197 AISCen_US
dc.identifier.startpage1440en_US
dc.identifier.endpage1446en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.authorscopusid56007700700-
dc.authorscopusid54405086400-
dc.authorscopusid55902625100-
dc.authorscopusid55948252100-
dc.identifier.scopusqualityQ4-
item.grantfulltextnone-
item.openairetypeConference Object-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.languageiso639-1en-
item.cerifentitytypePublications-
crisitem.author.dept02.09. Department of Industrial Engineering-
crisitem.author.dept02.09. Department of Industrial Engineering-
Appears in Collections:Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections
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