A human-intuitive fuzzy ranking approach with spread and skewness factors

It would be hard to deny the importance of fuzzy number ranking in fuzzy-based applications. The definition of fuzzy ranking, however, evades an easy description due to the overlapping of fuzzy sets. While many researchers have addressed this subject, close examination reveals that their results suffer from one or more shortcomings such as image-ranking problems or ranking two equally embedded fuzzy numbers with the same centroid and different spreads. This paper proposes a new fast and straightforward computational approach to ranking fuzzy numbers that aims to overcome such problems. The proposed approach considers several important factors such as spread, skewness and center, in addition to human intuition. Further, the proposed ranking approach involves a composition of these factors as demonstrated in the several examples provided and in comparison with other existing approaches.