Optimal location selection for electric vehicle car-sharing stations using Fermatean fuzzy decision-making methodology

Yildirim B., AYYILDIZ E., AYDIN N.

Journal of Cleaner Production, cilt.485, 2024 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 485
  • Basım Tarihi: 2024
  • Doi Numarası: 10.1016/j.jclepro.2024.144400
  • Dergi Adı: Journal of Cleaner Production
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Aerospace Database, Business Source Elite, Business Source Premier, CAB Abstracts, Chimica, Communication Abstracts, Compendex, INSPEC, Metadex, Pollution Abstracts, Public Affairs Index, Veterinary Science Database, Civil Engineering Abstracts
  • Anahtar Kelimeler: Car-sharing, Decision-making under uncertainty, Electric vehicle, Location selection, Multi-criteria decision-making, Sustainability
  • Karadeniz Teknik Üniversitesi Adresli: Evet

Özet

This study aims to determine the optimal location for electric vehicle (EV) car-sharing stations by introducing a Fermatean fuzzy multi-criteria evaluation approach. Selecting the optimal location for EV car-sharing stations is crucial for maximizing accessibility, convenience, and user adoption, promoting sustainable urban mobility. By strategically placing stations, the study demonstrates how environmental impacts can be minimized, traffic congestion reduced, and the efficiency of urban transportation improved. The proposed methodology integrates the Fermatean Fuzzy Pivot Pairwise Relative Criteria Importance Assessment (FF-PIPRECIA) method for weighting criteria with the Fermatean Fuzzy IseKriterijumska Optimizacija I Kompromisno Resenje (FF-VIKOR) method for ranking alternative locations, marking the first application of these techniques in combination. A decision matrix is constructed to standardize the evaluation of potential locations, enabling a structured comparison between alternatives. Furthermore, this study introduces the FF-PIPRECIA into decision-making literature, filling a gap by providing a robust tool for handling uncertainty in multi-criteria evaluations of sustainable transportation infrastructure. Key findings revealed that proximity to high-demand areas and energy infrastructure were among the most favorable criteria for selecting EV car-sharing locations. The method's effectiveness was validated by identifying optimal EV car-sharing locations contributing to sustainability and urban mobility goals. The findings offer valuable insights for urban planners and policymakers, enhancing the practical usability of multi-criteria decision-making methods in sustainable transportation planning.