A new intuitionistic fuzzy entropy and application in multi-attribute decision making

Abstract

In this paper, firstly, a new intuitionistic fuzzy (IF) entropy has been put forward, which considered both the uncertainty and the hesitancy degree of IF sets. Through comparing with other entropy measures, the advantage of the new entropy measure is obvious. Secondly, based on the new entropy measure, a new decision making method of a multi-attribute decision making problem was subsequently put forward, in which attribute values are expressed with IF values. In the cases of attribute weights, completely unknown and attribute weights are partially known. Two methods were constructed to determine them. One method is an extension of the ordinary entropy weight method, and the other method is a construction the optimal model according to the minimum entropy principle. Finally, two practical examples are given to illustrate the effectiveness and practicability of the proposed method.