Multiple attribute group decision-making method based on extended bipolar fuzzy MABAC approach

In this paper, we apply multiple attribute border approximation area comparison approach to multiple attribute group decision-making with bipolar fuzzy numbers (BFNs). We reconsider the notion of BFNs and propose its corresponding operational rules, score and accuracy functions. Further, we introduce two aggregation operators and develop an MADM approach based on conventional BABAC model with overall BFNs. The proposed technique is valid and accurate for considering the conflicting attributes. We analyse the proposed method by considering a numerical example for the selection of renewable energy power generation project to show the effectiveness of the developed approach. At last, we compare the developed approach with some existing operators to show its efficiency.