A Decision-Making Framework Based on 2-Tuple Linguistic Fermatean Fuzzy Hamy Mean Operators

Aggregation operators are useful tools for approaching situations in the realm of multiattribute decision-making (MADM). Among most valuable aggregation strategies, Hamy mean (HM) operator is designed to capture correlations among integral parameters. In this article, a series Hamy-inspired used combine 2-tuple linguistic Fermatean fuzzy (2TLFF) information. The new 2TLFF that born from adaptation include (2TLFFHM) operator, weighted (2TFFWHM) dual (2TLFFDHM) and (2TLFFWDHM) operator. Furthermore, various essential theorems stated, special cases these thoroughly examined. Then, renewed group (MAGDM) technique based on suggested provided. A practical example corroborates usefulness implementability technique. Finally, merits proposed MAGDM method demonstrated by comparing it with existing approaches, namely, can deal problems considering interactions multiple attributes 2TLFFWHM