The triangular fuzzy multiplicative preference relation (TFMPR) has attracted the attention of many scholars. This paper investigates the geometric consistency of TFMPR and applies it to group decision making (GDM). Firstly, by introducing two parameters, a triangular fuzzy number is transformed into an interval. According to the geometric consistency of interval multiplicative preference relation (IMPR), the geometric consistency of TFMPR is defined. Then, two corresponding IMPRs are extracted from the TFMPR by programming models in the majority case and minority case, respectively. Using the constructed linear programming models, two interval priority weight vectors are obtained from the two extracted IMPRs, respectively. Combining two interval priority weight vectors, a linear programming model is established to derive the triangular fuzzy priority weights. Subsequently, the closeness degrees of alternatives by experts are defined to obtain the group utility indices and individual regret indices of alternatives. Then, the compromise indices of alternatives are calculated considering experts’ compromise attitude. By minimizing the compromise indices of alternatives, a multi-objective programming model is constructed to obtain experts’ weights. By aggregating the individual TFMPRs, the collective TFMPR is obtained to derive the triangular fuzzy priority weights. Using the arithmetic mean values, the ranking order of alternatives is generated. Therefore, a method is proposed to solve GDM with TFMPRs. Finally, a performance evaluation example of precise poverty alleviation is provided to illustrate the advantage of the proposed method.

三角模糊乘积偏好关系（TFMPR）引起了许多学者的关注。本文研究了TFMPR的几何一致性，并将其应用于群体决策（GDM）。首先，通过引入两个参数，将三角模糊数转换为区间。根据区间乘积偏好关系（IMPR）的几何一致性，定义了TFMPR的几何一致性。然后，分别通过在大多数情况下和少数情况下的编程模型从TFMPR中提取两个相应的IMPR。使用构造的线性规划模型，分别从两个提取的IMPR中获得两个区间优先权重向量。结合两个区间优先权重向量，建立线性规划模型以导出三角模糊优先权。随后，定义专家的替代方案的接近程度，以获得替代方案的群体效用指数和个人后悔指数。然后，考虑专家的妥协态度，计算出替代方案的妥协指数。通过最小化替代方案的折衷指数，构建了多目标规划模型以获得专家的权重。通过汇总各个TFMPR，可以获取总TFMPR，以得出三角模糊优先级权重。使用算术平均值，生成替代项的排名顺序。因此，提出了一种用TFMPR解决GDM的方法。最后，