An Alternative Approach for Enhanced Decision-Making using Fermatean Fuzzy Sets
DOI:
https://doi.org/10.31181/sems21202411jKeywords:
Fermatean Fuzzy Sets, Multi-Criteria Decision-Making, Score function, Function Aggregation, Uncertainty, Decision-makersAbstract
This paper explores an innovative approach to solving multi-criteria decision-making (MCDM) problems by focusing on the aggregation of membership and non-membership values using score functions of Fermatean fuzzy sets. Fermatean fuzzy sets have been used to provide a more complex and flexible framework for decision-making because of their ability to handle higher levels of uncertainty and ambiguity. The suggested approach makes use of the unique characteristics of Fermatean fuzzy sets to enhance the aggregation procedure and guarantee a more accurate representation of uncertainty in scenarios involving decision-making. The study begins with a comprehensive review of existing fuzzy set theories and their applications in MCDM, highlighting the limitations of traditional methods. The novel part of this work is to provide a score function designed for Fermatean fuzzy sets that improves the accuracy and consistency of the aggregation procedure. Such score function offers a reliable method for combining several criteria since they are carefully put together to represent the varied relationships between membership and non-membership values. To validate the effectiveness of the proposed approach, the methodology is applied to a hypothetical case study in software design. The results underscore the potential of Fermatean fuzzy sets in addressing the complexities of MCDM, particularly in fields requiring high levels of precision and adaptability. This research presents a novel and effective alternative to traditional MCDM approaches, offering significant improvements in the handling of uncertainty and ambiguity. Experimental results of the study are presented and compared with the existing literature.
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