Intuitionistic fuzzy MABAC method based on cumulative prospect theory for multiple attribute group decision making

Intuitionistic fuzzy sets are often employed to depict complex and uncertain environments. The purpose of this article is to construct a new approach for dealing with multiattribute group decision making (MAGDM) problems. In this paper, we introduce the concept of cumulative prospect theory (CPT) into the original multiattributive border approximation area comparison (MABAC) method and create the intuitionistic fuzzy MABAC method based on CPT (CPT-IF-MABAC method). The new CPT-IF-MABAC method not only has fairly strong operability, but also inherits the characteristic of CPT that considers the influence of decision makers' attitude. Furthermore, this new model mixes together the determination method of attribute weight and alternative. At the end, the stability and availability of this method are demonstrated through an application instance about cold chain and the comparison with the existing methods, such as IF-MULTIMOORA method and IF-VIKOR method. In the future, we devote ourselves to explore more applications of this new proposed method and other more effective solutions for MAGDM.

Automated summary

This article introduces a new method, CPT-IF-MABAC, based on cumulative prospect theory for multiattribute group decision making. The method combines attribute weight determination and alternative selection, providing strong operability and considering decision makers' attitudes. Through a case study and comparison with existing methods, the stability and availability of the method are demonstrated, with a focus on exploring more applications and effective solutions for MAGDM in the future.