Trapezoidal-Valued Intuitionistic Fuzzy ELECTRE method based on Hamacher Weighted Averaging Aggregation Operator and its Application to Charging Station Site Selection for Electric Vehicles

This work presents a novel decision-making framework based on the trapezoidal-valued intuitionistic fuzzy Hamacher weighted averaging aggregation operator, incorporating variations of the ELECTRE method. This operator is designed to manage the ambiguity and inherent uncertainty that characterize complex decision-making scenarios, especially when making qualitative judgments. We apply this operator to the problem of locating electric vehicle (EV) charging stations, demonstrating its practical application. The framework captures the degrees of hesitance among decision-makers and their inclinations toward membership and non-membership values. Utilizing the adaptability of trapezoidal-valued intuitionistic fuzzy sets, our objective is to enhance the accuracy and robustness of the Hamacher aggregation process for multi-criteria decision-making (MCDM) problems. An illustrative example is provided to evaluate potential EV charging station locations based on criteria such as price, accessibility, expected demand, and environmental impact. The outcomes demonstrate the effectiveness of the TrVIFHWAA operator in aggregating expert opinions to improve decision-making in uncertain environments. Finally, sensitivity and comparative analyses were conducted to validate the method’s efficacy and robustness.