A Parameterized Intuitionistic Fuzzy Distance Measure-Based CoCoSo Method and Its Application in Stock Selection

In this paper, a parameterized intuitionistic fuzzy distance measure-based combined compromise solution (PIFDM-CoCoSo) framework is proposed to solve the multi-criteria decision-making (MCDM) problem with completely unknown criterion weight information. Firstly, a new parameterized intuitionistic fuzzy distance measure dλ is proposed. This measure dynamically adjusts the evaluation of individual and group consensus information by introducing the parameter λ. Numerical examples show the discriminative ability of the proposed distance measure for intuitionistic fuzzy information. On the basis of dλ, a new intuitionistic fuzzy entropy measure is derived to determine the objective criterion weight. Secondly, the two proposed measures are integrated into the comprehensive compromise solution framework to form the PIFDM-CoCoSo model. Finally, the proposed PIFDM-CoCoSo model is applied to the stock selection case. Sensitivity analysis and comparative analysis verify the robustness and effectiveness of the optimal solution. The proposed parameterized measure and ensemble model provide a flexible and effective tool for dealing with complex MCDM problems under intuitionistic fuzzy uncertainty.