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，常常假设专家是诚实和专业的。但这并不是团体决策框架（如群体层次分析法（GAHP））中的一个或多个专家尝试操纵其结果时的情况。本文的目的是在GAHP中引入两个启发式算法，允许检测操纵者并通过减少其权重来最小化其对群体共识的影响。第一种启发式算法基于这样一个假设，即操纵者提供的判断可以被认为是与组中其他专家的判断相对应的离群值。第二种启发式算法假定不诚实的判断比组的平均一致性更低。这两种方法都有数字示例和模拟。