Comparative Multi-Criteria Analysis to Determine Optimal Construction Locations for Electrical Vehicle Charging Stations

Anbarcı, Murat; Öz, Burak · 2026 · Crossref

DOI: 10.31466/kfbd.1686031

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Summary

This study addresses the critical challenge of determining optimal locations for electric vehicle (EV) charging stations to support the transition from fossil-fuel vehicles to zero-emission transport, a goal mandated by international climate agreements signed by thirty countries, including Türkiye. The strategic placement of charging infrastructure is essential for promoting EV adoption, yet it constitutes a complex multi-criteria decision-making (MCDM) problem involving conflicting qualitative and quantitative factors. The authors propose a comparative model using four distinct MCDM techniques—VIKOR, MOORA, Grey Relational Analysis (GRA), and DEMATEL—to evaluate potential sites, aiming to enhance decision reliability and support sustainable urban mobility planning. The methodology integrates expert judgment with spatial data and Geographic Information Systems (GIS). The study focuses specifically on social accessibility criteria, evaluating potential locations based on their proximity to amenities such as malls, places of worship, schools, health centers, and municipal buildings in the Sultanbeyli District of Istanbul. This focused approach prioritizes user convenience and experiential quality, positing that proximity to auxiliary activities increases station attractiveness and utilization. Data were collected from expert surveys, remote sensing, and satellite imagery to construct decision matrices. The four selected methods were applied to assign weights to criteria and rank alternative locations. VIKOR was used to find compromise solutions, MOORA for ratio-based optimization, GRA for handling limited or uncertain information, and DEMATEL to visualize causal relationships among criteria. The study also included sensitivity analysis to test the robustness of the rankings by varying criteria weights. The paper details the mathematical procedures for each technique, highlighting their specific strengths and limitations. VIKOR is noted for maximizing group benefit while minimizing individual regret, though it relies on subjective parameters. MOORA offers computational efficiency for quantitative data but assumes equal criterion weights unless adjusted. GRA is effective for small sample sizes but involves subjective coefficient selection. DEMATEL provides structural modeling of criterion interdependencies. A comparative analysis indicates that while each method has distinct applicability—such as MOORA for rapid evaluation and GRA for uncertain data—their parallel application enhances the transparency and resilience of the final decision. The results identify optimal charging station locations within the Sultanbeyli district based on these social accessibility metrics, providing a validated ranking of alternatives. The significance of this research lies in its contribution to strategic infrastructure planning by demonstrating that a comparative MCDM approach yields more robust outcomes than single-method analyses. By isolating social accessibility factors, the study provides policymakers, urban planners, and utility providers with actionable insights for expanding EV infrastructure in a way that aligns with user preferences and behavioral patterns. The findings support equitable and efficient deployment of charging stations, thereby facilitating the broader adoption of electric vehicles and contributing to national and global carbon reduction targets.

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