A novel entropy proposition for spherical fuzzy sets and its application in multiple attribute decision-making

Abstract

The inherent vagueness and uncertainty in reaching decisions are effectively coped with fuzzy logic and the concept of spherical fuzzy sets is one of the latest developments in this area. The hesitancy of decision-maker(s) about an attribute can be represented more extensively since the squared sum of membership, nonmembership, and hesitancy degrees should be between 0 and 1 while each degree should be defined in [0, 1]. In this study, we propose a novel entropy measure for spherical fuzzy sets and show its ability to provide the required properties. Then its usage in determining objective attribute weights is shown in an application of SF-WASPAS (Spherical Fuzzy extension of Weighted Aggregated Sum Product Assessment) on an illustrative problem. The robustness of the novel entropy's usage as an objective weighting tool is demonstrated by comparing the ranking solution of the proposed SF-WASPAS with the rankings obtained by SF-TOPSIS, SF-VIKOR, and SF-CODAS. © 2020 Elsevier B.V., All rights reserved.