To obtain reliable results of expertise, which usually use individual and group expert pairwise comparisons, it is important to summarize (aggregate) expert estimates provided that they are sufficiently consistent. There are several ways to determine the threshold level of consistency sufficient for aggregation of estimates. They can be used for different consistency indices, but none of them relates the threshold value to the requirements for the reliability of the expertise's results. Therefore, a new approach to determining this consistency threshold is required. The proposed approach is based on simulation modeling of expert pairwise comparisons and a targeted search for the most inconsistent among the modeled pairwise comparison matrices. Thus, the search for the least consistent matrix is carried out for a given perturbation of the perfectly consistent matrix. This allows for determining the consistency threshold corresponding to a given permissible relative deviation of the resulting weight of an alternative from its hypothetical reference value.

翻译：为获得可靠的专家评估结果（通常采用个体与群体专家两两比较），在确保专家估计具有足够一致性的前提下进行汇总（聚合）至关重要。现有多种方法可用于确定估计聚合所需的充分一致性阈值水平。这些方法适用于不同的一致性指标，但均未将阈值与专家评估结果可靠性的要求相关联。因此，需要一种确定该一致性阈值的新方法。本文提出的方法基于专家两两比较的仿真建模，以及对建模所得两两比较矩阵中最不一致矩阵的定向搜索。具体而言，该方法针对完全一致矩阵的给定扰动，搜寻其中一致性最弱的矩阵。通过这种方式，可确定与替代方案最终权重相对于其假设参考值的给定允许相对偏差相对应的具体一致性阈值。