q-Rung orthopair fuzzy dynamic aggregation operators with time sequence preference for dynamic decision-making

The q -rung orthopair fuzzy set (q-ROPFS) is a kind of fuzzy framework that is capable of introducing significantly more fuzzy information than other fuzzy frameworks. The concept of combining information and aggregating it plays a significant part in the multi -criteria decision -making method. However, this new branch has recently attracted scholars from several domains. The goal of this study is to introduce some dynamic q -rung orthopair fuzzy aggregation operators (AOs) for solving multi -period decision -making issues in which all decision information is given by decision makers in the form of "q -rung orthopair fuzzy numbers"(q-ROPFNs) spanning diverse time periods. Einstein AOs are used to provide seamless information fusion, taking this advantage we proposed two new AOs namely, "dynamic q -rung orthopair fuzzy Einstein weighted averaging (DQROPFEWA) operator and dynamic q -rung orthopair fuzzy Einstein weighted geometric (DQROPFEWG) operator". Several attractive features of these AOs are addressed in depth. Additionally, we develop a method for addressing multi -period decision -making problems by using ideal solutions. To demonstrate the suggested approach's use, a numerical example is provided for calculating the impact of "coronavirus disease"2019 (COVID-19) on everyday living. Finally, a comparison of the proposed and existing studies is performed to establish the efficacy of the proposed method. The given AOs and decision -making technique have broad use in real -world multi -stage decision analysis and dynamic decision analysis.