Singularly Perturbed Initial Value Problem for First Order Delay Differential Equation Magdm Problem using a Magdm Problem

Abstract

This paper presents a novel approach to Dynamic Intuitionistic Fuzzy Multiple Attribute Group Decision Making (DIF-MAGDM) problems, where decision attributes are represented by intuitionistic fuzzy numbers collected over multiple time periods. To determine the unknown decision-maker weights, a singularly perturbed initial value problem is formulated, incorporating a transition parameter τ for computing the weighting vectors. The proposed method employs the Dynamic Intuitionistic Fuzzy Weighted Averaging (DIFWA) operator to transform all dynamic intuitionistic fuzzy decision matrices into a column matrix. To rank and select the most suitable alternative, a proximity coefficient function is applied. The effectiveness and practicality of the approach are demonstrated through a numerical case study on supplier selection. The results validate the robustness and applicability of the proposed decision-making framework in dynamic and uncertain environments.