Circular Intuitionistic Fuzzy Median Ranking Model with a Novel Scoring Mechanism for Multiple Criteria Decision Analytics

This study aims to pioneer an innovative circular intuitionistic fuzzy (C-IF) scoring-mediated median ranking model designed for multiple criteria decision analytics. The primary goal is to establish a comprehensive precedence ranking for competing alternatives, effectively addressing the inherent uncertainties present in decision-analytic challenges within the C-IF environment. The core content delves into the creation of an original scoring mechanism tailored to navigate the complexities of C-IF uncertainties. Moreover, the research introduces a specialized C-IF median ranking model for decision analytics, leveraging the foundational concept of the C-IF scoring mechanism. A significant contribution is made through the formulation of a robust implementation procedure, specifically tailored for the seamless operation of the C-IF scoring-mediated median ranking model within the framework of C-IF information. Drawing from the suggested C-IF scoring mechanism, this research introduces novel concepts related to comprehensive C-IF scoring functions and comprehensive disagreement metrics. Subsequently, a comprehensive disagreement matrix is formulated, with its entries quantifying the extent of disagreement in assigning specific ranks to each alternative across all criterion-wise precedence relationships. This paves the way for the development of a new C-IF scoring-mediated median ranking model, offering decision analysts a tool to navigate intricate C-IF information and derive dependable decision-analytic outcomes.