Interval-valued Pythagorean Fuzzy EDAS method: An Application to Car Selection Problem

Classical multi-criteria decision making (MCDM) methods have been extended to their fuzzy versions under uncertainty in the literature. Besides, these ordinary fuzzy MCDM methods have been further extended to their new versions through the recently developed types of ordinary fuzzy sets. This study extends the evaluation based on distance from the average solution (EDAS) method by using interval-valued Pythagorean fuzzy numbers to solve fuzzy multi-criteria group decision-making problems with a larger membership domain providing more flexibility. An illustrative example of the car selection problem is given to show the effectiveness and applicability of the proposed model and results are compared with intuitionistic interval-valued fuzzy EDAS method. A sensitivity analysis is also performed to reveal the effect of the weights on alternative rankings.