A graphical method for ranking Atanassov's intuitionistic fuzzy values using the uncertainty index and entropy

Many different types of ranking methods based on the score and accuracy functions of intuitionistic fuzzy values (IFVs) exist in the literature. The notion of knowledge bases, as in the case of rough set theory, is very handy to show that every ranking technique produces a unique classification of IFVs with a unique order among the classes. This means these rankings give rise to unique knowledge bases. Therefore, ranking of IFVs by two or more distinct techniques may produce different results. In this study, a graphical ranking method based on the uncertainty index and entropy is proposed. This approach is tested on several numerical examples existing in the literature and shown to be intuitive and convenient for applications in real-life scenarios.