A comprehensive decision-making framework for the electric vehicle charging station location problem

The rapid adoption of electric vehicles (EVs) is essential for reducing air pollution and achieving environmental sustainability. However, the inefficient placement of electric vehicle charging stations (EVCSs) can limit accessibility, increase costs, and reduce overall system efficiency, thereby slowing EV adoption. This study addresses the complex challenge of optimally locating EVCSs by evaluating and ranking candidate sites using a comprehensive multi-criteria framework. To select the optimal site location, 66 criteria were considered, comprising 55 factors identified from the literature and 11 additional criteria proposed by experts. A novel hybrid multi-criteria decision-making (MCDM) method was introduced to prioritize candidate locations systematically. Additionally, fuzzy theory was applied to handle uncertainty in decision-making processes. The proposed MCDM was validated through a real-world case study. The results indicate that “Income Rate,” “Greenhouse Gases Emission Reduction,” and “Investment Pay-back Period” are the most influential factors in EVCS site selection.