A Novel Multi- Expert Mabac Method Based on Fermatean Fuzzy Sets
In recent years, new forms of ordinary fuzzy sets have been introduced. Developed forms of fuzzy sets aim to identify the uncertainty thoroughly and get better maximizing outcomes. Fermatean fuzzy sets are one of the newly developed forms of ordinary fuzzy sets that identify the uncertainty comprehensively. Decision-making process uses some mathematical methods and methodologies providing experts to make the correct decision. One of these methods, the MABAC method, is based on computing the distance between each alternative and the bored approximation area. However, decision-making processes also involves ambiguity and vagueness that the fuzzy sets and fuzzy decision-making strategies can easily manage while crisp methods may not. Therefore, we aimed to propose a novel method based on MABAC method with Fermantean fuzzy sets. To achieve this aim, we briefly reviewed basic theories of Fermantean fuzzy sets. Moreover, Fermantean fuzzy MABAC method was constructed, and the steps of the decision-making process were clarified. An illustrative example is given to show the applicability of the proposed method. Additionally, comparative analyses and sensitivity analysis were conducted. As a result, we demonstrate that our model can handle the decision-making process effectively and efficiently.
Keyword: MADM problems, MABAC, Fermatean fuzzy sets, Fermatean fuzzy weighted average operators, Fermatean fuzzy weighted geometric operators, Fermatean fuzzy MABAC method