Multi-Attribute Decision-Making with Independent Trapezoidal Intuitionistic Fuzzy Information Based on Risk Orientation and Similarity Measure

Abstract

The strategy production in intuitionistic fuzzy multi-attribute decision-making is influenced by various factors. More realistic data representations are needed to portray ambiguity under increasingly complex decision-making contexts. Firstly, this study proposes a new approach for ranking independent trapezoidal intuitionistic fuzzy numbers based on the risk attitudes of decision-makers. The proposed ranking approach incorporates the decision-makers’ risk preferences and considers all possible values in the feasible domain. After that, a novel similarity measure between two independent trapezoidal intuitionistic fuzzy numbers is presented based on the three-segment projection. The constructed similarity measure uses the image structure of the data to reflect the variation of vagueness and then also combines deviation to achieve optimization. Moreover, this study improves the VIKOR method under the independent trapezoidal intuitionistic fuzzy environment (V-ITIFE) to solve the multi-attribute decision-making problems. Finally, a numerical example is presented to illustrate the applicability and efficiency of the V-ITIFE method.