Integrated AHP–Entropy–Game Theory and GIS framework for EV charging station site selection
Transportation Research Part D: Transport and Environment, cilt.161, 2026 (SCI-Expanded, SSCI, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 161
- Basım Tarihi: 2026
- Doi Numarası: 10.1016/j.trd.2026.105608
- Dergi Adı: Transportation Research Part D: Transport and Environment
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, Applied Science & Technology Source, Compendex, EconLit, Environment Index, Geobase, INSPEC, Public Affairs Index, Academic Search Ultimate (EBSCO), Business Source Ultimate (EBSCO), Engineering Source (EBSCO)
- Anahtar Kelimeler: Electric vehicle charging stations, Game theory, Geographic information systems, Multi-criteria decision making, Site selection
- İstanbul Üniversitesi Adresli: Evet
Özet
The rapid growth of electric mobility requires robust frameworks for optimal electric vehicle charging station (EVCS) deployment. This study proposes an integrated spatial decision-support framework combining the Analytic Hierarchy Process (AHP), Entropy Weight Method (EWM), game-theoretic deviation-minimization weighting, and Geographic Information Systems (GIS) to identify suitable EVCS locations in İzmir, Türkiye. The approach integrates literature-informed AHP-based prioritization with entropy-derived analytical weighting for balanced multi-criteria spatial analysis. Results show that proximity to electricity transmission lines receives the highest weight and should be interpreted as an infrastructure-proximity and potential grid-connection feasibility proxy, rather than a direct measure of grid capacity or electricity-system adequacy. Population density and major accessibility factors, including main roads and transport stations, contribute to suitability as indirect demand and mobility proxies. Highly suitable zones are mainly concentrated in central and northern districts (Konak, Karşıyaka, Bornova, Bayraklı), covering 6.51 % of the area, while 17.08 % is classified as suitable.