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,通常的假设是专家的诚实和专业。然而,在团体决策框架下,如团体层次分析过程(GAHP),这不是事实,因为一个或多个专家试图操纵结果以符合他们的利益。本文旨在介绍GAHP设置中的两个启发式方法,以便检测操纵者并通过减少他们的权重来最小化他们对群体共识的影响。第一种启发式方法是基于这样一个假设,即操纵者提供的判断可以被认为是与群体中其他专家判断相比的异常值(outliers)。第二种启发式方法假设,不诚实的判断比群体平均水平的一致性低。两种方法都用数字例子和模拟进行说明。