A hybrid multi-criteria group decision methodology based on fairly operators and EDAS method under interval-valued Fermatean fuzzy environment

The conception of interval-valued Fermatean fuzzy set (IVFFS) provides a wider range for decision expert to express their uncertain and vague assessment by interval membership grade (MG) and non-membership grade (NMG). The purpose of this study is to build up a novel multiple criteria group decision-making (MCGDM) methodology to solve the new energy vehicle battery supplier (NEVBS) selection problem under interval-valued Fermatean fuzzy circumstance. To begin with, two novel interval-valued Fermatean fuzzy fairly operators are propounded based on the fairly operations to aggregate interval-valued Fermatean fuzzy numbers (IVFFNs). Then, the weights of decision expert are attained based on the combination of subjective linguistic assessment model and similarity-based method. Besides, an integrated criteria weight determination model is created based the subjective weight ascertained by stepwise weight assessment ratio analysis (SWARA) method and subjective weight ascertained by symmetry point of criterion (SPC) model with interval-valued Fermatean fuzzy information. The fusion weight of criteria is determined using the principle of relative entropy. Further, a hybrid MCGDM methodology through incorporating the SWARA, SPC and evaluation based on distance from average solution (EDAS) methods is proposed to attain the prioritization of NEVBSs. Lastly, an illustrative case that selects the optimal NEVBS is implemented to verify the feasibility and applicability of the proposed MCGDM methodology. The comparison investigation is executed to illustrate the effectiveness and merits of the developed method in handling complex decision problems.