An extended MABAC method for multi-criteria group decision-making problems based on correlative inputs of intuitionistic fuzzy information

Abstract

This study aims to introduce a series of novel distance measures of an intuitionistic fuzzy set and an extended Multi-attributive Border Approximation Area Comparison method to address multi-criteria group decision-making problems. To aggregate the intuitionistic fuzzy information, we propose two aggregation operators, namely, the intuitionistic fuzzy Dombi generalised λ-Shapley Choquet arithmetical average operator and intuitionistic fuzzy Dombi generalised λ-Shapley Choquet geometric average operator. These aggregation operators consider the importance of combinations and correlations among combinations of input arguments. Furthermore, an illustrative example of a human resource management problem is presented to verify the effectiveness of the proposed method, and sensitivity and comparison analyses are conducted to demonstrate the technique’s stability and advancements. Finally, conclusions are drawn.