In the decision making methods the common assumption is the honesty and professionalism of experts. 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 judgments of the rest of the experts in the group. Second heuristic assumes that dishonest judgments are less consistent than average consistency of the group. Both approaches are illustrated with numerical examples and simulations.

翻译：在决策方法中，通常假设专家具有诚实性和专业性。然而，在群体决策框架（如群体层次分析法，GAHP）中，当一名或多名专家试图操纵结果以牟取私利时，这一假设便不再成立。本文旨在引入两种GAHP环境下的启发式方法，以检测操纵者并通过降低其权重来最小化他们对群体共识的影响。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判断的异常值；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模拟进行验证。