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

被引:0
|
作者
Yildirim, Betul [1 ]
Ayyildiz, Ertugrul [2 ,3 ]
Aydin, Nezir [4 ,5 ]
机构
[1] Hasan Kalyoncu Univ, Dept Ind Engn, Gaziantep, Turkiye
[2] Karadeniz Tech Univ, Dept Ind Engn, Trabzon, Turkiye
[3] Western Caspian Univ, Dept Comp Sci, Baku, Azerbaijan
[4] Hamad Bin Khalifa Univ, Coll Sci & Engn, Doha, Qatar
[5] Yildiz Tech Univ, Dept Ind Engn, Istanbul, Turkiye
关键词
Car-sharing; Electric vehicle; Sustainability; Location selection; Multi-criteria decision-making; Decision-making under uncertainty; RELOCATION PROBLEM; CHARGING STATIONS; SYSTEMS; DESIGN; VIKOR; FRAMEWORK; MODEL; FLEET;
D O I
10.1016/j.jclepro.2024.144400
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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.
引用
收藏
页数:15
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