A multicriteria group decision-making approach based on interval-valued intuitionistic fuzzy sets: A comparative perspective

This study develops an approach to tackle multiple criteria group decision-making problems in the context of interval-valued intuitionistic fuzzy sets. Due to conflicting evaluations and insufficient information about the criteria, an interval-valued intuitionistic fuzzy preference relation matrix is employed to determine the relative importance of criteria in terms of pairwise comparisons. The decision matrix, which indicates the degree of alternatives with respect to each criterion, is expressed by interval-valued intuitionistic fuzzy numbers (IVIFNs). In order to integrate interval-valued intuitionistic fuzzy information, some special aggregation operators are created by altering the aggregation operation of IVIFNs. The three families of parametric fuzzy unions and fuzzy intersections are applied in the aggregation operation with comparisons of the ranking results of alternatives. With a linear programming method, the proposed approach uses an optimization model to obtain criterion weights in exact numbers rather than intervals, and subsequently calculates an aggregated IVIFN for each alternative. The score function and accuracy function assist in discriminating between the aggregated IVIFNs, and in generating a final rank of alternatives. Finally, an illustrative supplier selection problem is used to demonstrate how to apply the proposed approach and to observe the computational consequences resulting from various aggregation operators. The results reveal that the parameters of the aggregation operators indeed have an impact on the ranks of alternatives.