Location selection for logistics center with fuzzy SWARA and CoCoSo methods

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dc.authoridTOPAL, AYSE/0000-0003-1882-4545
dc.authoridUlutas, Alptekin/0000-0002-8130-1301
dc.contributor.authorUlutas, Alptekin
dc.contributor.authorKarakus, Can Bulent
dc.contributor.authorTopal, Ayse
dc.date.accessioned2024-10-26T18:05:49Z
dc.date.available2024-10-26T18:05:49Z
dc.date.issued2020
dc.departmentSivas Cumhuriyet Üniversitesi
dc.description.abstractLogistics centers are home to many and varied facilities, such as storage, transportation of goods, handling, reassembling, clearing, disassembling, quality control, social services and providing accommodation, so on. Providing logistical activities from one location can provide some macro advantages, as well as regional development in developing countries. For the micro level, logistics center selection has an effective role in increasing the operational efficiency and decreasing the costs of the firms. While the wrong location selection for logistics center affects the operations and costs of the companies negatively, the optimal location selection increases the performance, competitiveness, profitability of the firms and reduces the costs of the firms. Since many different qualitative and quantitative criteria are considered in the selection of the logistics center, this selection problem is an MCDM problem. A new integrated MCDM model is proposed to solve this problem for Sivas province in Turkey. This study presents two contributions to the literature. Firstly, the number of studies related to CoCoSo method is limited in the literature, therefore, the CoCoSo method is proposed in this study. Secondly, a new integrated GIS-based MCDM model comprising fuzzy SWARA and CoCoSo is introduced to literature to address the location selection problem for a logistics center. In this study, the results of CoCoSo method and the resulfts of other MCDM methods (COPRAS, VIKOR, ARAS, MOORA, and MABAC) are compared to test the accuracy of results obtained by CoCoSo. Besides, the criteria weights are changed and the possible changes in the results are tracked.
dc.identifier.doi10.3233/JIFS-191400
dc.identifier.endpage4709
dc.identifier.issn1064-1246
dc.identifier.issn1875-8967
dc.identifier.issue4
dc.identifier.scopus2-s2.0-85176355755
dc.identifier.scopusqualityQ2
dc.identifier.startpage4693
dc.identifier.urihttps://doi.org/10.3233/JIFS-191400
dc.identifier.urihttps://hdl.handle.net/20.500.12418/29185
dc.identifier.volume38
dc.identifier.wosWOS:000534641700096
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherIos Press
dc.relation.ispartofJournal of Intelligent & Fuzzy Systems
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectCoCoSo
dc.subjectfuzzy SWARA
dc.subjectGIS
dc.subjectlogistics center
dc.subjectlocation selection
dc.subjectMCDM
dc.titleLocation selection for logistics center with fuzzy SWARA and CoCoSo methods
dc.typeArticle

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