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Robustness threshold methodology for multicriteria based ranking using imprecise data

机译:基于不精确数据的基于多标准排序的稳健性阈值方法

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It is well established that making decisions from defined data according to various criteria requires the use of MultiCriteria Decision Aiding or Analysis (MCDA) methods. However the necessary input data for these approaches are often ill-known especially when the data are a priori estimated. The common MCDA approaches consider these data as singular/scalar values. This paper deals with the consideration of more realistic, values by studying the impact of imprecision on a classical “precise” ranking established with ACUTA, a method based on additive utilities. We propose a generic approach to establish the concordance of pairwise relations of preference despite interval-based imprecision by complementing ACUTA with a computation of Kendall's index of concordance and of a threshold for maintaining this concordance. The methodology is applied to an industrial case subjected to Sustainable Development problems.
机译:很好地确定,根据各种标准从定义数据做出决策需要使用多标语决策协助或分析(MCDA)方法。然而,这些方法的必要输入数据通常是毫不疑问,特别是当数据估计数据时尤其是难以清楚的。常见的MCDA方法将这些数据视为奇异/标量值。本文通过研究不确定对与Acuta建立的经典“精确”排名的影响来审议更现实的值,这是一种基于附加公用事业的方法。我们提出了一种通用的方法,尽管通过补充ACUTA的间隔的不精确来建立一致的偏好关系的一致性,但通过计算KENDALL的一致性指数和保持这种一致性的阈值来实现acuta。该方法适用于经历可持续发展问题的工业案例。

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