Novel similarity measure for interval-valued intuitionistic trapezoidal fuzzy numbers

Interval-valued intuitionistic fuzzy numbers serve as a comprehensive and flexible tool to present uncertain or vague information. Such an information is of utmost importance in expert and knowledge-based systems, primarily utilized to model the practical problems concerning decision-making, clustering analysis and pattern recognition. Theoretically, this paper contributes to the generalization of interval-valued intuitionistic fuzzy numbers and suggests a novel similarity measure in the proposed framework of generalized interval-valued intuitionistic trapezoidal fuzzy numbers. The advantage of proposed measure over an existing comparable similarity measure has been established using illustrative examples. Furthermore, the application of the proposed method in a decision-making problem demonstrates its practicality. © Bharati Vidyapeeth's Institute of Computer Applications and Management 2025.