LAUSR

This paper aims to develop an aggregation operator for two‐tuple linguistic information based on utility function, which characterizes the influence of decision makers' psychological factors on the linguistic aggregation process. First, we propose a new two‐tuple linguistic ordered utility aggregation (TOU) operator, and then, we investigate its properties that are suitable for any utility function. Subsequently, we derive a specific form of the TOU operator, which is called the two‐tuple linguistic generalized ordered weighted utility averaging‐hyperbolic absolute risk aversion (TOHU) operator, under the hyperbolic absolute risk aversion utility function. Then, we further investigate its families including a wide range of aggregation operators. To determine the weights of the TOHU operator, which take the form of two‐tuple linguistic, we establish an optimization weighting model by combining the information of input arguments and subjective considerations of decision makers. Furthermore, we propose a two‐tuple linguistic aggregation method to deal with the multiple attribute group decision‐making (MAGDM) problem based on the TOHU operator. Finally, we provide an example to demonstrate the application of the TOHU operator to MAGDM.