A Decision-Making Approach Based on New Aggregation Operators under Fermatean Fuzzy Linguistic Information Environment

Fermatean fuzzy linguistic (FFL) set theory provides an efficient tool for modeling a higher level of uncertain and imprecise information, which cannot be represented using intuitionistic (IFL)/Pythagorean (PFL) sets. On the other hand, scale function (LSF) is better way to consider semantics terms during evaluation process. It worth noting that existing operational laws aggregation operators (AOs) numbers (FFLNs) are not valid in many situations, can generate errors real-life applications. The present study aims define new robust AOs under environment. To do so, first, we some modified FFLNs based on LSF prove important mathematical properties them. Next, work defines several AOs, namely, FFL-weighted averaging (FFLWA) operator, geometric (FFLWG) FFL-ordered weighted (FFLOWA) (FFLOWG) FFL-hybrid (FFLHA) operator (FFLHG) Several these investigated detail. Further, proposed decision-making approach with information developed solve group problems multiple attributes. Finally, illustrate effectiveness approach, supplier selection problem presented where alternatives given FFLNs. Compared methods, salient features (1) it qualitative data FFLNs; (2) attitudinal character decision-makers solution process; (3) has solid ability distinguish optimal alternative.