Information Measures-Based Multi-criteria Decision-Making Problems for Interval-Valued Intuitionistic Fuzzy Environment

Abstract

In the present communication, new entropy and divergence measures are developed for interval-valued intuitionistic fuzzy sets and compared it with the existing measures. Numerical result reveals that the proposed entropy measure attains the accurate classification, which illustrates their efficiency. Further, to cope with the multi-criteria decision-making problems with non-commensurable and conflicting criteria, an extended VIKOR method is developed under interval-valued intuitionistic environment. On the basis of proposed divergence measure, the particular measure of closeness of each alternative is calculated to the interval-valued intuitionistic fuzzy positive ideal solution. To illustrate the applicability of the proposed method, a multi-criteria decision-making problem of supplier selection is discussed under incomplete and uncertain information situation, which employs its advantages and feasibility.