Intuitionistic fuzzy multi-criteria decision-making method based on evidential reasoning

An approach based on interval belief degrees and fuzzy evidential reasoning analytical algorithm is developed for multi-criteria decision problems with uncertainties. The criteria weights are represented by interval numbers and criteria values by triangular intuitionistic fuzzy numbers. The proposed approach does not need to utilize the theories such as arithmetic operations for Triangular intuitionistic fuzzy numbers, for it can remove the influence of the limitations existed in the arithmetic operations. A numerical example is also provided to illustrate the rationality and utility of the proposed method.

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► The ER approach using interval belief degrees is introduced to model triangular intuitionistic fuzzy numbers with interval belief structures.
► The fuzzy ER analytical algorithm is developed for MCDM problems with triangular intuitionistic fuzzy numbers and incomplete information.
► The non-linear programming models are constructed based on criteria weights intervals, belief degrees intervals and ER analytical algorithm.
► The genetic algorithm is employed to solve the non-linear models yielding the minimal and maximal fuzzy utilities of each alternative.
► Theories such as arithmetic operations of triangular intuitionistic fuzzy numbers which are not always rational, are not involved.