Multicriteria group decision-making (MCGDM), with the strong uncertainty and randomness, has always been a hotspot in the world. The chief purpose of the paper is to address the problem with Atanassov’s interval-valued intuitionistic fuzzy sets (AIVIFSs), Z-numbers, and trapezium clouds. First, some related concepts and former operators of AIVIFSs, Z-numbers, and trapezium clouds are reviewed, meanwhile, AIVIFSs and Z-numbers are synthesized to come up with a novel linguistic expression. Then, Z-trapezium-trapezium cloud (ZTTC) is proposed to quantify the linguistic evaluation information to avoid excessive computation caused by traditional methods. Later, a new approach of calculating the objective weight vector is presented based on entropy weight method (EWM). To take the huge advantages of technique for order preference by similarity to ideal solution (TOPSIS) method in ranking, 2-norm in mathematical theory is applied to derive a way of calculating the distance between different ZTTCs. Finally, an example about the grade assessment of coronavirus Disease 2019 (COVID-19) is given. For further confirming the validity and feasibility, sensitivity analysis and comparison with other methods are conducted.

具有高度不确定性和随机性的多准则小组决策（MCGDM）一直是世界范围内的热点。本文的主要目的是解决Atanassov的区间值直觉模糊集（AIVIFS），Z值和梯形云的问题。首先，对AIVIFS，Z数和梯形云的一些相关概念和以前的运算符进行了综述，同时，对AIVIFS和Z数进行了合成以提出一种新颖的语言表达。然后，提出了Z-梯形-梯形云（ZTTC）来量化语言评估信息，以避免传统方法引起的过多计算。随后，提出了一种基于熵权法（EWM）的目标权重向量计算新方法。为了利用排序上的与理想解决方案（TOPSIS）方法相似的方法来获得顺序偏爱技术的巨大优势，应用数学理论中的2范数推导了计算不同ZTTC之间距离的方法。最后，给出了有关2019年冠状病毒疾病（COVID-19）等级评估的示例。为了进一步确认其有效性和可行性，进行了敏感性分析并与其他方法进行了比较。