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For intuitionistic fuzzy values (IFVs), there are more or less some drawbacks in the existing comparison methods, so it is necessary for us to develop a more proper technique for comparing or ranking IFVs in this paper. To do so, we first formalize an IFV as a fuzzy subset in order to analyze the fuzzy meaning of an IFV, and then according to the basic properties of the fuzzy subset, we determine the dominance relation (order relation) between two IFVs by defining a dominance degree. In order to explain the feasibility of the dominance relations, we validate the monotonicity of intuitionistic fuzzy operational laws, and additionally, we improve and prove the monotonicity of several intuitionistic fuzzy aggregation operators on the basis of the dominance relations. Because it is of importance for some practical problems (e.g., intuitionistic fuzzy multi-attribute decision making) to rank IFVs, we finally develop a method for ranking IFVs by constructing a dominance matrix based on the dominance degrees. A simple example is taken to illustrate the validity of our ranking method.

In fuzzy decision-making environments, intuitionistic preference relation is highly useful in depicting uncertainty and vagueness of preference information provided by the decision maker. In the process of decision making with intuitionistic preference relation, the most crucial issue is how to derive the ranking of alternatives from intuitionistic preference relation. In this article, we investigate the ranking methods of alternatives on the basis of intuitionistic preference relation from various angles, which are based on the intuitionistic fuzzy ordered weighted averaging operator, the intuitionistic fuzzy ordered weighted geometric operator, the uncertain averaging operator, the uncertain geometric operator, the uncertain ordered weighted averaging operator, and the uncertain ordered weighted geometric operator, respectively, and study their desirable properties. Moreover, we give a numerical analysis of the developed ranking methods by a practical example, and finally discuss further research directions.

Considering the decision maker’s psychological state will influence their evaluation result in the risky multi-attribute decision-making problem, and the uncertainty of evaluation information. In this paper, we will propose a behavioral risky multiple attribute decision making with interval type-2 fuzzy ranking method and TOPSIS method. The interval type-2 fuzzy set is used to express the uncertainty of evaluation information, the prospect theory is applied to describe people’s psychological state in the processing of risk decision making. First, we define a new ranking method for interval type-2 fuzzy set to compare the interval type-2 fuzzy evaluation information and the expectation. Second, we give a relative distance for interval type-2 fuzzy set to get the distance between the interval type-2 fuzzy evaluation information and expectation. Third, we use the prospect theory, the new defined ranking method and the new defined distance formula to obtain the comprehensive prospect value. Fourth, we use the improved TOPSIS method and the comprehensive prospect value to rank the alternatives. Based on the above-mentioned steps, we give the solution for risky interval type-2 fuzzy multiple attribute decision-making problem, which named as the behavioral risky multiple attribute decision making with interval type-2 fuzzy ranking method and TOPSIS method. Finally, we use an example to show the rationality of this method.