Study Of Multiple Attribute Decision Making Problems Based On Intuitionistic Fuzzy Information

The ways of using the theory of Cantor set to describe things in the real world are quite alternative, being unable to deal with vague and uncertain information and data. Zadeh proposed the theory of fuzzy set, which extends the characteristic function valuing from 1 or 0 to the membership function valuing within the closed interval [0, 1]. The proposition of this theory provides us with an efficient way of describing vague phenomena. It is a pity that although this theory has been widely applied in many fields of the social life, it has confronted with more and more restriction and challenges as it cannot covey the whole information of the object. Intuitionistic fuzzy set is an extension of Zadeh's fuzzy set. Intuitionistic fuzzy set considers simultaneously such three factors as the degree of membership, non-membership and hesitation, hence provides more choices for describing things and is more capable of expressing uncertainty than traditional fuzzy set. In a word, Intuitionistic fuzzy set is more practical than traditional fuzzy set.This thesis, on the basis of introducing the existed intuitionistic fuzzy set theory, makes a deep and systematic study on the distance measure of intuitionistic fuzzy set. The distance measure is a key point of the theory of intuitionistic fuzzy set which has been attached great importance by many scholars in and abroad, and many scholars have proposed different measuring ways. Based on analyzing the existed distance measure, this thesis introduces some improved distance measures. And after proving the good qualities of them, the author applies them in the multiple attribute decision-making problems of intuitionistic fuzzy information.