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.
Highlights
For multi-attributes decision problems, such as supplier selection, material selection in manufactory and evaluation of firm’s safety performance, it is necessary to consider many factors simultaneously.This makes the problem become complex and it is difficult to find the best solution
Many intuitionistic fuzzy (IF) multi-attribute decision making (MADM) methods are developed to deal with these situations [16,17,18]
Szmidt and Kacprzyk [24] (2001) first axiomatized intuitionistic fuzzy entropy measure, which is an extension of the De Luca and Termini axioms [20] in 1972 for fuzzy sets
Summary
School of Information Management, Jiangxi University of Finance and Economics, Nanchang School of Software, Jiangxi University of Science and Technology, Nanchang 330013, China These authors contributed equally to this work. Received: 7 August 2014; in revised form: 1 November 2014 / Accepted: 4 November 2014 /
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