Abstract
The increasing environmental pollution has led to the need to accelerate interest in electric vehicles. It is crucial to specify locations for electric vehicle charging stations (EVCSs) to meet the charge demand. The question that arises here is how to make a comprehensive evaluation of the alternative EVCS locations regarding sustainability. This study presents a new integrated group multi-criteria decision making (MCDM) approach for a robust evaluation of alternative EVCS locations. Two different group aggregation techniques (GATs) are applied to obtain the aggregated weights with AHP (analytical hierarchy process): aggregating individual judgments and aggregating individual priorities. For ranking alternative locations, two MCDM methods, TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and MOORA (Multi-Objective Optimization on the Basis of Ratio Analysis) were applied for both aggregated weights. Furthermore, we introduce two types of rankings from the sensitivity analysis based on the most selected alternatives for each rank position and the most selected rank position for each alternative. Finally, an integrated ranking is obtained by combining the results of group MCDM methods and sensitivity analysis to investigate the impact of GATs and MCDM methods. The proposed methodology is applied to rank the EVCS locations in Bursa, Turkey, with four main criteria and eight sub-criteria. The similarity measure results indicate that the GAT and the MCDM method have an impact on the evaluation scores and the rankings. The integrated group MCDM approach provides a comprehensive evaluation of the alternatives.
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Acknowledgements
We would like to thank BTK, Eşarj, EMRA, G-Charge Inc., GDH, and TEIAS Institutions and employees for their valuable interest in this study and the data support provided. Hilal Yılmaz is supported by the Turkish Council of Higher Education (CoHE) under the 100/2000 PhD scholarship program.
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Yagmahan, B., Yılmaz, H. An integrated ranking approach based on group multi-criteria decision making and sensitivity analysis to evaluate charging stations under sustainability. Environ Dev Sustain 25, 96–121 (2023). https://doi.org/10.1007/s10668-021-02044-1
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DOI: https://doi.org/10.1007/s10668-021-02044-1