An extended group decision-making algorithm with intuitionistic fuzzy set information distance measures and their applications

Abstract

The intuitionistic fuzzy set is a generalization of the fuzzy set that performs noticeably better in expressing and managing uncertainty. The amount that one intuitionistic fuzzy set differs from the others is given by the distance measure. Certain distance measures that have been suggested by the various researchers do not satisfy the axioms of distance measures and also be counter-intuitive circumstances. In this paper we present a novel distance measure for intuitionistic fuzzy sets that is based on the difference between the cross-evaluation factor’s minimum and maximum, the membership degree and non-membership degree, respectively. The proposed measure satisfies all the axiomatic properties and also resolves the counter-intuitive cases. Consequently, this study provides an efficient symmetric distance formula for determining the distance between the information contained by intuitionistic fuzzy sets. By using numerical examples, it is shown that the new measurement is reliable. Also, we provide pattern recognition algorithms and employ them to solve diagnostic-related problems in medicine.