Picture fuzzy entropy : a novel measure for managing uncertainty in multi-criteria decision-making

Entropy plays a vital role within fuzzy set theory as it quantifies the level of uncertainty present in the data. This study proposes a novel entropy measure tailored for Picture Fuzzy Sets (PIFS). This entropy measure is formulated based on the axioms developed for PIFS entropy, ensuring its suitability for such sets. We use a validation process to ascertain the effectiveness of this proposed measure. Furthermore, a compelling example is presented to demonstrate the practical application of entropy measures in real-world scenarios involving Multi-Criteria Decision-Making (MCDM). The findings underscore the significance of entropy measures in proficiently managing uncertainty and accommodating diversity. The proposed entropy measure is an invaluable tool for making well-informed decisions when confronted with intricate decision-making situations