Location selection for logistics center with fuzzy SWARA and CoCoSo methods


JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, vol.38, no.4, pp.4693-4709, 2020 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 38 Issue: 4
  • Publication Date: 2020
  • Doi Number: 10.3233/jifs-191400
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Communication Abstracts, Compendex, Computer & Applied Sciences, INSPEC, Metadex, zbMATH, Civil Engineering Abstracts
  • Page Numbers: pp.4693-4709
  • Keywords: CoCoSo, fuzzy SWARA, GIS, logistics center, location selection, MCDM, MULTIPLE CRITERIA, SUPPLY CHAIN, DECISION, TOPSIS, VIKOR, AHP
  • Inonu University Affiliated: Yes


Logistics 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.