A new integrated grey mcdm model : Case of warehouse location selection

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dc.authorid0000-0002-8130-1301tr
dc.contributor.authorUlutaş, Alptekin
dc.contributor.authorBalo, Figen
dc.contributor.authorSua, Lutfu
dc.contributor.authorDemir, Ezgi
dc.contributor.authorTopal, Ayşe
dc.contributor.authorJakovljević, Vladimir
dc.date.accessioned2022-05-11T06:21:12Z
dc.date.available2022-05-11T06:21:12Z
dc.date.issued2021tr
dc.departmentİktisadi ve İdari Bilimler Fakültesitr
dc.description.abstractWarehouses link suppliers and customers throughout the entire supply chain. The location of the warehouse has a significant impact on the logistics process. Even though all other warehouse activities are successful, if the product dispatched from the warehouse fails to meet the customer needs in time, the company may face with the risk of losing customers. This affects the performance of the whole supply chain therefore the choice of warehouse location is an important decision problem. This problem is a multicriteria decision-making (MCDM) problem since it involves many criteria and alternatives in the selection process. This study proposes an integrated grey MCDM model including grey preference selection index (GPSI) and grey proximity indexed value (GPIV) to determine the most appropriate warehouse location for a supermarket. This study aims to make three contributions to the literature. PSI and PIV methods combined with grey theory will be introduced for the first time in the literature. In addition, GPSI and GPIV methods will be combined and used to select the best warehouse location. In this study, the performances of five warehouse location alternatives were assessed with twelve criteria. Location 4 is found as the best alternative in GPIV. The GPIV results were compared with other grey MCDM methods, and it was found that GPIV method is reliable. It has been determined from the sensitivity analysis that the change in criteria weights causes a change in the ranking of the locations therefore GPIV method was found to be sensitive to the change in criteria weightstr
dc.identifier.citationUlutaş, A., Balo, F., Sua, L., Demir, E., Topal, A., & Jakovljević, V. (2021). A new integrated grey mcdm model: case of warehouse location selection. Facta Universitatis, Series: Mechanical Engineering, 19(3), p. 515-535.tr
dc.identifier.doi10.22190/FUME210424060Uen_US
dc.identifier.endpage535tr
dc.identifier.issn0354-2025
dc.identifier.issue3tr
dc.identifier.scopus2-s2.0-85117179464en_US
dc.identifier.scopusqualityQ1
dc.identifier.startpage515tr
dc.identifier.urihttps://hdl.handle.net/20.500.12418/12762
dc.identifier.volume19tr
dc.identifier.wosWOS:000704914500009en_US
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherFaculty of Mechanical Engineeringtr
dc.relation.ispartofFacta Universitatis, Series: Mechanical Engineeringen_US
dc.relation.publicationcategoryUluslararası Hakemli Dergide Makale - Kurum Öğretim Elemanıtr
dc.rightsinfo:eu-repo/semantics/openAccesstr
dc.subjectGrey PSItr
dc.subjectMCDMtr
dc.subjectGrey PIVtr
dc.titleA new integrated grey mcdm model : Case of warehouse location selectionen_US
dc.typeArticleen_US

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