Fermatean Fuzzy Aggregation Operators with Priority Degrees and their Applications

Abstract

Fermatean fuzzy numbers (FrFNs) have demonstrated significant utility in real-world scenarios for handling uncertain data. In this study, we focus on multi-criteria decision-making (MCDM) problems with prioritized parameters. To address this, we introduce the notion of "priority levels." By assigning non-negative real numbers, known as "priority degrees," to these priority levels, we establish aggregation operators (AOs). Our work puts forth a diverse set of prioritized operators, notably the Fermatean fuzzy prioritized averaging (FrFPAd) operator with priority degrees and the Fermatean fuzzy prioritized geometric (FrFPGd) operator with priority degrees. Through systematic comparisons, we highlight the superiority of our proposed methodology over other contemporary approaches already in use. We place particular emphasis on thoroughly investigating the influence of priority degrees on the overall decision-making outcomes. This analysis yields valuable insights into the implications and benefits of incorporating prioritization in MCDM. Furthermore, we provide a decision-making strategy based on the aforementioned operators, within the Fermatean fuzzy set environment. This strategy offers a practical framework for effective decision-making when faced with uncertainty.