Hybrid multiple attribute group decision making involves ranking and selecting competing courses of action available using attributes to evaluate the alternatives. The decision makers assessment information can be expressed in the form of real number, interval-valued number, linguistic variable, and the intuitionistic fuzzy number. All these evaluation information can be transformed to the form of intuitionistic fuzzy numbers. A combined GRA with intuitionistic fuzzy group decision-making approach is proposed. Firstly, the hybrid decision matrix is standardized and then transformed into an intuitionistic fuzzy decision matrix. Then, intuitionistic fuzzy averaging operator is utilized to aggregate opinions of decision makers. Intuitionistic fuzzy entropy is utilized to obtain the entropy weights of the criteria, respectively. After intuitionistic fuzzy positive ideal solution and intuitionistic fuzzy negative ideal solution are calculated, the grey relative relational degree of alternatives is obtained and alternatives are ranked. In the end, a numerical example illustrates the validity and applicability of the proposed method. 1. Introduction Multiattribute decision making is an important issue in modern society, which is to select an appropriate option from a set of feasible alternatives with respect to the features of all predefined attributes. It often involves multiple decision makers, multiple selection criteria, and subjective and imprecise assessments. The attribute values given by the decision maker (or expert) over the alternatives under each attribute may not be all described by exact numbers, and sometimes they may take the following forms, such as exact numerical values, interval numbers, triangular fuzzy numbers, linguistic labels, and intuitionistic fuzzy numbers. Quite a number of research work have been done to solve the multiattribute decision making problems where the attributes take one of the former forms over the last decades [1–4]. In some real-life situations, a decision maker’s (DM’s) preferences for alternatives may not be expressed accurately due to the fact that DM may not possess a precise level of knowledge and the DM is unable to express the degree to which one alternative is better than others. In such cases, the DM may provide his/her preferences with a degree of doubt. Intuitionistic fuzzy set introduced by Atanassov [5–9] which is a generalization of the concept of Zadeh’s fuzzy set [10] and is more suitable to deal with these cases than fuzzy sets. Intuitionistic fuzzy set is characterized by a membership function and
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