A novel modified Delphi-based spherical fuzzy AHP integrated spherical fuzzy CODAS methodology for vending machine location selection problem: a real-life case study in İstanbul


Neural Computing and Applications, 2023 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Publication Date: 2023
  • Doi Number: 10.1007/s00521-023-09063-1
  • Journal Name: Neural Computing and Applications
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Applied Science & Technology Source, Biotechnology Research Abstracts, Compendex, Computer & Applied Sciences, Index Islamicus, INSPEC, zbMATH
  • Keywords: AHP, CODAS, Location selection, Spherical fuzzy, Vending machine
  • Yıldız Technical University Affiliated: Yes


Timely delivery of products to customers is the great importance for retailers in supply chain management. Vending machines are one of the most effective retail tools for consumers to get the product they want at any time. With the developing technology, retailers tend to establish distribution with vending machines to provide faster service to the consumer. At this point, one of the primary objectives is to make the location selection decisions for these vending machines. The most suitable location selection decision includes the evaluation of each alternative under the specified criteria in a problem where there are multiple alternative locations. The present paper proposes a novel modified Delphi-based spherical fuzzy analytical hierarchy process (SFAHP) integrated spherical fuzzy combinative distance-based assessment (SFCODAS) methodology to the vending machine location selection (VMLS) problem. After determining the main and sub-criteria hierarchically, the Modified Delphi method is used to consolidate the opinions of the experts regarding the criteria and integrate them into the study. The main and sub-criteria weights are provided by the SFAHP method. And the most suitable location is determined by the SFCODAS method by ranking among the alternative locations according to these weighted criteria. The case study of VMLS is presented for a retail firm in Istanbul. Sensitivity analysis is performed to measure the flexibility of the proposed methodology. To validate the applicability of the proposed methodology, comparison analysis is presented with the results of the spherical fuzzy weighted aggregated sum-product assessment (SFWASPAS) method. Finally, the conclusions and future directions are discussed in the study.