Characterizing continuous (s, S) policy with supplier selection using Simulation Optimization

Basit Öğe Kaydı
dc.authoridDosdogru, Ayse Tugba/0000-0002-1548-5237
dc.authoridFARUK, GEYIK/0000-0001-8732-0629
dc.authoridGOCKEN, Mustafa/0000-0002-1256-2305
dc.contributor.authorGocken, Mustafa
dc.contributor.authorDosdogru, Ayse Tugba
dc.contributor.authorBoru, Asli
dc.contributor.authorGeyik, Faruk
dc.date.accessioned2025-01-06T17:37:12Z
dc.date.available2025-01-06T17:37:12Z
dc.date.issued2017
dc.description.abstractA real-world inventory control system, due to its nonlinear, stochastic, time-dependent nature, and the presence of complex interactions between supply chain members, can become quite challenging to optimize and requires a complex model. At this point, the Simulation Optimization (SO) model gains a better understanding of the complex and messy phenomenon of the inventory control of supply chain members. By creating SO models for Distribution Center (DC)s and Suppliers, we wish to present flexible and comprehensible research on the important decision of whether to minimize the differences between total overordering cost and total underordering cost (Model 1) or to minimize the total supply chain cost (Model 2). We also try to point out several important issues: the optimal value of the initial inventory, the reorder point, and the order-up-to level in continuous (s, S) policy for each DC and each Supplier; whether SO models can successfully integrate the supplier selection and continuous (s, S) policy for the supply chain environment; how to apply statistical analysis skills to compare these SO models with a greater level of detail. According to the cost analysis, the total supply chain cost of Model 1 is improved approximately 22% with Model 2. Also, Model 2 is the best one according to quantity-based analysis, order-based analysis, probability-based analysis, and lead-time-based analysis. Model 2 can be successfully applied for the actual situation of the supply chain inventory system and companies can obtain a remarkable amount of saving while increasing their competitive edge.
dc.description.sponsorshipScientific and Technological Research Council of Turkey (TUBITAK) [2211]
dc.description.sponsorshipAyse T Dosdogru gratefully acknowledges the Scientific and Technological Research Council of Turkey (TUBITAK) for the 2211 scholarship program.
dc.identifier.doi10.1177/0037549716687044
dc.identifier.endpage396
dc.identifier.issn0037-5497
dc.identifier.issn1741-3133
dc.identifier.issue5
dc.identifier.scopus2-s2.0-85015087692
dc.identifier.scopusqualityQ2
dc.identifier.startpage379
dc.identifier.urihttps://doi.org/10.1177/0037549716687044
dc.identifier.urihttps://hdl.handle.net/20.500.14669/2132
dc.identifier.volume93
dc.identifier.wosWOS:000400137800002
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherSage Publications Ltd
dc.relation.ispartofSimulation-Transactions of The Society For Modeling and Simulation International
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241211
dc.subjectContinuous (s, S) policy
dc.subjectinventory control system
dc.subjectsupplier selection
dc.subjectSimulation Optimization
dc.titleCharacterizing continuous (s, S) policy with supplier selection using Simulation Optimization
dc.typeArticle

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu