A New Divergence Measure for Intuitionistic Fuzzy Matrices

Distance / similarity measures facilitate in decision-making by identifying the discrimination or similarity between two or more course of actions to identify the best decision. Data available in the real world may not be in a crisp format. Intuitionistic fuzzy matrices are applicable managing uncertainty and useful in decision making, relational equation, clustering, etc. To take decision the divergence between two intuitionistic fuzzy matrices identifies dissimilarity between matrices. This paper presents a new divergence measure for intuitionistic fuzzy matrices with the verification of its validity. The fundamental properties are demonstrated for the new intuitionistic fuzzy divergence measure. A technique to solve multi-criteria decision-making problems is developed by utilizing the proposed intuitionistic fuzzy divergence measure. Finally, application in the medical diagnosis of this intuitionistic fuzzy divergence measure to decision making is shown using real data. © 2023 Slovene Society Informatika. All rights reserved.