Abstract
With respect to intuitionistic fuzzy multiple attribute decision making problems with preference information on alternatives and incomplete weight information, a method based the minimum deviation is proposed. Firstly, some operational laws of intuitionistic fuzzy numbers, score function and accuracy function of intuitionistic fuzzy numbers are introduced. Then, to reflect the decision maker's preference information, an optimization model based on the minimum deviation method, by which the attribute weights can be determined, is established. For the special situations where the information about attribute weights is completely unknown, we establish another optimization model. By solving this model, we get a simple and exact formula, which can be used to determine the attribute weights. We utilize the intuitionistic fuzzy weighted averaging (IFWA) operator to aggregate the intuitionistic fuzzy information corresponding to each alternative, and then rank the alternatives and select the most desirable one(s)...
Highlights
Atanassov [1,2,3] introduced the concept of intuitionistic fuzzy set (IFS), which is a generalization of the concept of fuzzy set [4]
In the process of intuitionistic fuzzy MADM with preference information on alternatives, sometimes, the attribute values and preference values on alternatives take the form of intuitionistic fuzzy numbers, and the information about attribute weights is incompletely known or completely unknown because of time pressure, lack of knowledge or data, and the expert’s limited expertise about the problem domain
Minimum Deviation Models (IFWA) operator to aggregate the intuitionistic fuzzy information corresponding to each alternative, and rank the alternatives and select the most desirable one(s) according to the score function and accuracy function
Summary
Atanassov [1,2,3] introduced the concept of intuitionistic fuzzy set (IFS), which is a generalization of the concept of fuzzy set [4]. Hong and Choi [8] provided another technique for handling multiple attribute fuzzy decision making problems based on vague set theory, they provided new functions to measure the degree of accuracy in the grades of membership of each alternative with respect to a set of attribute. They assumed that the degree of importance to each attribute is constant. Lin [21] presented a new method for handling multiple attribute fuzzy decision making problems, where the characteristics of the alternatives are represented by intuitionistic fuzzy sets.
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