A new ranking method for trapezoidal intuitionistic fuzzy numbers and its application to multi-criteria decision making

The ranking of intuitionistic fuzzy numbers is paramount in the decision making process in a fuzzy and uncertain environment. In this paper, a new ranking function is defined, which is based on Robust's ranking index of the membership function and the non-membership function of trapezoidal intuitionistic fuzzy numbers. The mentioned function also incorporates a parameter for the attitude of the decision factors. The given method is illustrated through several numeri-cal examples and is studied in comparison to other already-existent methods. Starting from the new classification method, an algorithm for solving fuzzy multi-criteria decision-making (MCDM) problems is proposed. The application of said algorithm implies accepting the subjectivity of the deciding factors, and offers a clear perspective on the way in which the subjective attitude influ-ences the decision-making process. Finally, a MCDM problem is solved to outline the advantages of the algorithm proposed in this paper.

Automated summary

In this paper, a new ranking function for trapezoidal intuitionistic fuzzy numbers is proposed, based on Robust's ranking index. The function also incorporates a parameter for the attitude of the decision factors. The effectiveness of the method is illustrated through numerical examples and an algorithm for solving fuzzy multi-criteria decision-making problems is proposed.