The 2-dimensional uncertain linguistic variable (2DULV) can depict decision-makers’ subjective assessments on the reliability of given evaluation results, which is a valid and practical tool to express decision information. In this study, we develop an improved MABAC method with 2DULVs to handle multiattribute group decision-making (MAGDM) problems where the weight information of attributes is unknown. First, some related theories of 2DULVs and the basic procedure of the MABAC method are briefly reviewed. Then, the maximum comprehensive evaluation value method is extended to 2DULVs to obtain combination weights of attributes, in which the subjective weights are determined according to the best–worst method (BWM) and the objective weights are calculated by the maximum deviation method. Besides, the generalized weighted average operator for 2DULVs (2DULGWA) is utilized to aggregate the evaluation information given by all experts. Finally, an improved MABAC for 2DULVs (2DUL-MABAC) is proposed, and an example is carried out to explain the validity of the proposed approach.

二维不确定语言变量（2DULV）可以描述决策者对给定评估结果的可靠性的主观评估，这是表达决策信息的有效且实用的工具。在这项研究中，我们开发了一种带有2DULV的改进的MABAC方法，以处理属性权重信息未知的多属性组决策（MAGDM）问题。首先，简要回顾了2DULV的一些相关理论和MABAC方法的基本过程。然后，将最大综合评估值方法扩展到2DULV，以获得属性的组合权重，其中，根据最佳/最差方法（BWM）确定主观权重，并通过最大偏差法计算目标权重。除了，2DULV的广义加权平均算子（2DULGWA）用于汇总所有专家给出的评估信息。最后，提出了一种用于2DULV的改进型MABAC（2DUL-MABAC），并通过一个例子说明了该方法的有效性。