Generalized and Group-Generalized Parameter Based Fermatean Fuzzy Aggregation Operators with Application to Decision-Making

Fermatean fuzzy set (FRFS) is very helpful in representing vague information that occurs in real world circumstances. Their eminent characteristic of FRFS is that the degree of membership ^ and degree of nonmembership ^ satisfy the condition 0 ^³ (x) +^³ (x) 1, so the space of vague information they can describe is broader. This study introduces the concept of generalized parameters into the FRFS framework and proposes a set of generalized Fermatean fuzzy average aggregation operators for the purpose of information aggregation. Subsequently, the operators are expanded to encompass a generalized parameter based on group consensus, which is derived from the perspectives of numerous experienced senior experts and observers. The present study offers a multi-criteria decision-making (MCDM) methodology, which is demonstrated using a numerical example to successfully showcase the suggested technique. In conclusion, a comparative study is undertaken to validate the efficacy of the suggested technique in relation to existing methodologies.