In decision-making methods, it is common to assume that the experts are honest and professional. However, this is not the case when one or more experts in the group decision making framework, such as the group analytic hierarchy process (GAHP), try to manipulate results in their favor. The aim of this paper is to introduce two heuristics in the GAHP, setting allowing to detect the manipulators and minimize their effect on the group consensus by diminishing their weights. The first heuristic is based on the assumption that manipulators will provide judgments which can be considered outliers with respect to those of the rest of the experts in the group. The second heuristic assumes that dishonest judgments are less consistent than the average consistency of the group. Both approaches are illustrated with numerical examples and simulations.

翻译：在决策方法中，通常假设专家是诚实且专业的。然而，当群体决策框架（如群体层次分析法，GAHP）中的一个或多个专家试图操纵结果以谋取私利时，情况并非如此。本文旨在引入GAHP设置中的两种启发式方法，通过降低操纵者的权重来检测其行为并最小化其对群体共识的影响。第一种启发式方法基于以下假设：操纵者提供的判断可被视为相对于群体中其他专家的异常值。第二种启发式方法假设不诚实判断的一致性低于群体平均一致性。两种方法均通过数值示例和仿真进行说明。