Modified EDAS Method Based on Cumulative Prospect Theory for Multiple Attributes Group Decision Making with Interval-valued Intuitionistic Fuzzy Information

TL;DR

This paper introduces a modified EDAS decision-making method that incorporates cumulative prospect theory and interval-valued intuitionistic fuzzy information to better handle uncertainty and psychological factors in group decision making.

Contribution

It extends the classical EDAS method by integrating CPT and IVIFSs, providing a new approach for multi-attribute group decision making under uncertainty.

Findings

The proposed IVIF-CPT-MABAC method effectively handles fuzzy and uncertain information.

Numerical example demonstrates improved decision stability and effectiveness.

Comparative analysis shows advantages over traditional methods.

Abstract

The Interval-valued intuitionistic fuzzy sets (IVIFSs) based on the intuitionistic fuzzy sets combines the classical decision method is in its research and application is attracting attention. After comparative analysis, there are multiple classical methods with IVIFSs information have been applied into many practical issues. In this paper, we extended the classical EDAS method based on cumulative prospect theory (CPT) considering the decision makers (DMs) psychological factor under IVIFSs. Taking the fuzzy and uncertain character of the IVIFSs and the psychological preference into consideration, the original EDAS method based on the CPT under IVIFSs (IVIF-CPT-MABAC) method is built for MAGDM issues. Meanwhile, information entropy method is used to evaluate the attribute weight. Finally, a numerical example for project selection of green technology venture capital has been given and some comparisons is used to illustrate advantages of IVIF-CPT-MABAC method and some comparison analysis and sensitivity analysis are applied to prove this new methods effectiveness and stability.