Multi-attribute Group Decision Making Method with Unknown Attribute Weights Based on the Q-rung Orthopair Uncertain Linguistic Power Muirhead Mean Operators

Q-rung orthopair uncertain linguistic sets (q-ROULSs) are a powerful tool for describing ambiguity and uncertainty of information. In this study, considering that in most multi-attribute group decision making (MAGDM) problems, not only the quantitative evaluation information makers but also qualitative opinions should be considered. Therefore, we develop novel MAGDM method with unknown attribute weights under q-rung environments. We firstly propose cross-entropy q-ROULSs, which is utilized to solve optimal by linear programming model. order effectively summarize unclear language extend power Muirhead mean (PMM) operator family othpair (q-ROULPMM) operators. The advantage PMM it mitigates adverse effects too high or low values on results, takes into account interrelationships between values. At same time, some ideal properties special cases q-ROULPMM studied. Further, new based proposed aggregation operators developed solving problem q-ROULSs. Finally, carried out numerical experiments prove effectiveness superiority