Multi-criteria decision analysis model using the q-rung orthopair fuzzy similarity measures and the COPRAS method for electric vehicle charging station site selection

Site selection for electric vehicle charging station (EVCS) plays an important role in promoting electric vehicle industry development. With the involvement of uncertainty and several factors, a proper site selection for EVCS can be considered as a multi-criteria decision analysis (MCDA) problem. Thus, the aim of this paper is to propose a new MCDA method based on the combination of similarity measure, complex proportional assessment (COPRAS) approach and q-rung orthopair fuzzy sets (q-ROFSs). In this method, the criteria weights are computed through similarity measure-based formula, whereas the rank of the EVCS sites is evaluated through the proposed COPRAS method under the context of q-ROFSs. For this purpose, some new similarity measures are proposed to quantify the degree of similarity between q-ROFSs, which can overcome the drawbacks of existing q-rung orthopair fuzzy similarity measures. Some numerical examples are discussed to show the effectiveness of the proposed measures over the existing q-rung orthopair fuzzy similarity measures. Further, the classical COPRAS method is extended into the context of q-ROFSs and combined with the similarity measure-based weighting formula. To prove the usefulness of the proposed method, it is implemented on a case study of EVCS site selection. Sensitivity analysis is discussed to confirm the stability of the obtained results. The robustness of the proposed method is emphasised in terms of comparison with the prior developed MCDA methods, which proves its advantages over the existing ones.