Novel Pythagorean Fuzzy Entropy for Selection of Vehicles’ Battery using VIKOR Approach

Over the past few decades, the widespread adoption of vehicle batteries (VBs) and allied technologies has garnered significant attention. The decision-making (DM) process for selecting efficient VBs is inherently challenging. This study addresses this challenge by introducing a new methodology entropy measure of Pythagorean fuzzy sets (PFSs) in conjunction with the Vlekriterijumsko Kompromisno Rangiranje (VIKOR) method to assess the efficiency of VBs. While exploring PFSs, previous studies have given limited attention to the entropy measures of PFSs. Therefore, this paper contributes by introducing novel entropy measure for PFSs. The extended method is employed to address Multi-criteria decision-making (MCDM) challenges involving PFSs, specifically when criteria weights are entirely unidentified. To enhance decision-making, decision-making experts devise new approaches based on extended procedures, including Pythagorean fuzzy (PF) entropy, to capture substantial degrees of decision-expert and criteria. The PF weighted averaging operator is utilized to integrate unique choice information into a cohesive group decision matrix. The aimed approach is illustrated through a case study involving the selection of VBs, where the assessment of batteries alternatives against each criterion is extracted using Pythagorean fuzzy numbers (PFN). The results demonstrate the efficacy of the PFVIKOR method in effectively selecting vehicles’ batteries.