Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14365/5044
Full metadata record
DC FieldValueLanguage
dc.contributor.authorSeyfi, S.A.-
dc.contributor.authorYanıkoğlu, İ.-
dc.contributor.authorYılmaz, Görkem-
dc.date.accessioned2023-12-26T07:28:57Z-
dc.date.available2023-12-26T07:28:57Z-
dc.date.issued2023-
dc.identifier.issn0254-5330-
dc.identifier.urihttps://doi.org/10.1007/s10479-023-05741-4-
dc.identifier.urihttps://hdl.handle.net/20.500.14365/5044-
dc.description.abstractThis study proposes a multi-stage stochastic production planning approach for a joint lot sizing and workforce scheduling problem under demand uncertainty. Scenario trees are used to model uncertainty in demand, and a multi-stage scenario-based stochastic linear program is developed. This model allows for both here-and-now and wait-and-see decisions providing flexibility for decision-makers to adjust production quantities according to the realized portion of demand and improve the overall effectiveness of production planning by better managing the number of active lines, workforce, and inventory levels. A matheuristic is developed for large-sized instances, which yields near-optimal solutions in practicable computation times. The proposed methods are demonstrated over a real data set taken from a Turkish home and professional appliances company, Vestel. The results show significant improvements in cost and CPU time performances for benchmark approaches, verifying the effectiveness of the proposed method. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.en_US
dc.description.sponsorshipTürkiye Bilimsel ve Teknolojik Araştırma Kurumu, TÜBİTAK: 119C142en_US
dc.description.sponsorshipThis research was supported by the Scientific and Technological Research Council of Turkey (TUBITAK) 2244 Industrial Ph.D. Fellowship Program under grant number 119C142. The authors thank the planning and R &D team of Vestel Home Appliances and Vestel Electronics for bringing the authors’ attention to the related problem and sharing the problem data. The authors also thank the two anonymous reviewers for their insightful comments and suggestions, which have significantly improved the overall quality of this research.en_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofAnnals of Operations Researchen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectMulti-stage decision makingen_US
dc.subjectProduction planningen_US
dc.subjectStochastic programmingen_US
dc.subjectWorkforce schedulingen_US
dc.titleMulti-stage scenario-based stochastic programming for managing lot sizing and workforce scheduling at Vestelen_US
dc.typeArticleen_US
dc.identifier.doi10.1007/s10479-023-05741-4-
dc.identifier.scopus2-s2.0-85179732383en_US
dc.departmentİzmir Ekonomi Üniversitesien_US
dc.authorscopusid58026479200-
dc.authorscopusid55927270000-
dc.authorscopusid57214665651-
dc.identifier.wosWOS:001126004700003en_US
dc.institutionauthor-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityQ2-
dc.identifier.wosqualityQ1-
item.grantfulltextreserved-
item.openairetypeArticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextWith Fulltext-
item.languageiso639-1en-
item.cerifentitytypePublications-
crisitem.author.dept05.09. Industrial Engineering-
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Files in This Item:
File SizeFormat 
5044.pdf
  Restricted Access
462.4 kBAdobe PDFView/Open    Request a copy
Show simple item record



CORE Recommender

SCOPUSTM   
Citations

1
checked on Nov 20, 2024

WEB OF SCIENCETM
Citations

1
checked on Nov 20, 2024

Page view(s)

66
checked on Nov 18, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.