Applications of multi-attribute group decision-making models under triangular interval-type 2 fuzzy to risk preference

Abstract Triangular interval type-2 fuzzy sets, which can handle data with greater ambiguity and uncertainty, can be created by extending type-1 fuzzy sets. They are defined by two membership functions, which are also fuzzy sets. The triangular interval type-2 fuzzy set's bottom and upper bounds are represented by the membership functions defined over the universe discourse. An improved fuzzy multi-attribute interval-valued approach to group decision-making that takes the decision-maker's risk preferences into account. The multi-attribute group decision-making problem can be resolved by using triangular interval type-2 fuzzy numbers since the attribute weight information is completely unknown. The triangular type 2 fuzzy entropy and the data from the group decision matrix are used to calculate the attribute and relative weights; the combination of similarity and proximity yields the decision-maker weight of each attribute; the formula for the triangular type 2 fuzzy distance measure yields the overall superiority of each scheme; comparison and sequencing determine which scheme is the best; and finally, a decision pertaining to the manufacturing company's supplier serves as an example to illustrate the rationale and effectiveness of the proposed strategy.