Complete ranking for generalized trapezoidal fuzzy numbers and its application in supplier selection using the GTrF-CoCoSo approach

Abstract

Decision-making is an indispensable tool in many real-life situations. The classical set theory is insufficient to solve problems involving uncertainty and qualitative data. In order to tackle scenarios with qualitative information and imprecise boundaries, fuzzy set theory generalizes crisp sets. Thus, ranking is an essential methodology in decision-making in a fuzzy environment. In literature, generalized trapezoidal fuzzy numbers (GTrFNs) are used to model many real-life situations with imprecise, uncertain, and incomplete information. There are various techniques available to discriminate arbitrary GTrFNs. Several researchers are seeking a standard consensus technique to distinguish between arbitrary GTrFNs. The diagonal distance right position, diagonal distance left chord, diagonal distance center position, diagonal distance, and diagonal distance right chord scores are the five score functions that are used in this work to develop a complete ranking (total ordering) principle on the class of GTrFNs to distinguish arbitrary GTrFNs. To show the potentiality of the proposed method, we compare the proposed approach with the few existing approaches suggesting to rank GTrFNs. Further, we proposed a new GTrF-CoCoSo approach by incorporating the proposed complete ordering principle. Then the efficacy of the proposed ranking principle is examined in solving multi-criteria decision-making (MCDM) using the GTrF-CoCoSo approach to select the best banana supplier for food production company. Furthermore, a sensitivity analysis is presented to evaluate the performance of the suggested ranking principle with the GTrF-CoCoSo approach.