Fuzzy Multiple Attribute Decision Making Method Based On Binary Semantics

Hesitant fuzzy linguistic term sets are suitable to deal with the situations where people have hesitancy in providing their linguistic assessments.The paper mainly studies the methods of multi-attribute decision making based on 2-tuple.It consists of four chapters:In chapter 1, we first introduce the origin and current research situations of decision making methods based on linguistic type and hesitant fuzzy linguistic sets.Then we list the main contributions of this paper.In chapter 2, we first introduce the notion of hesitant fuzzy 2-tuple sets(H2TS),and develop some operators for H2TS: H2T-WA operator, H2T-OWA operator and the H2T-WOWA operator.Applying these operators, we get the evaluation information corresponding to each alternative, then the alternatives are ranked by the score function and the variance function.This approach can deal with the attribute weights are known or unknown multi-attribute decision-making problems.In chapter 3, an approach based on a power average operator for hesitant fuzzy linguistic term set is proposed for multi-attribute decision-making problems, in which the evaluation information are mutual support hesitant fuzzy linguistic information.We first define the power operator of H2 TS.Based on the operator, we give a method to solve the group decision-making problem with mutual support hesitant fuzzy linguistic information. By the method, the linguistic assessments offered by experts are transformed into H2TS; then, the power average operator for hesitant fuzzy 2-tuple sets is used to get the group decision-making matrix and the TOPSIS method is applied for the ranking of alternatives. Finally, an illustrative example is given to demonstrate the practically and effectiveness of the proposed method.In chapter 3, a method based on the Choquet integral operator for hesitant fuzzy multi-attribute decision-making problems is proposed. Firstly, we promoted the Choquet integral operator to H2 TS.Then, we studied its properties.At last, the alternatives are ranked by the score function and the variance function of the H2 TS.This method can be used to solve the attributes of the relationship between the multiple attribute decision making problems.