A novel approach employing hesitant intuitionistic fuzzy linguistic Einstein aggregation operators within the EDAS...

The Evaluation based on Distance from Average Solution (EDAS) is a multi-criteria decision analysis (MCDA) technique that uses various distances from average values to make decisions. It bears resemblance to other distance-based approaches like SPOTIS, VIKOR or TOPSIS, except that instead of positive and negative ideal solutions, it uses an average solution. For hesitant intuitionistic fuzzy linguistic term sets (HIFLTSs), we first define several operational laws and aggregation operators. As a follow-up, the hesitating intuitionistic fuzzy linguistic Einstein weighted averaging (HIFLEWA) operator is introduced. In this study, the EDAS technique is used to address a multi-criteria group decision making (MCGDM) issue by utilizing the suggested operational laws and aggregation operators for HIFLTSs, aiming to mitigate the uncertainties of decision makers (DMs). A representative numerical example is employed to illustrate the strength and logical soundness of our proposed method in identifying the optimal choice under the given limitations. A comparison examination with the existing TOPSIS approach is also performed to ensure that the results generated with EDAS are accurate.