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首页> 外文期刊>Fuzzy Optimization and Decision Making: A Journal of Modeling and Computation Under Uncertainty >G-distance and G-decomposition for improving G-consistency of a Pairwise Comparison Matrix
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G-distance and G-decomposition for improving G-consistency of a Pairwise Comparison Matrix

机译:G距离和G-分解,用于提高成对比较矩阵的G-verionity

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摘要

Pairwise comparisons have been a long standing technique for comparing alternatives/criteria and their role has been pivotal in the development of modern decision making methods. Since consistency ensures rational decisions, in literature several approaches are proposed for the revision of the Pairwise Comparison Matrix in order to improve its consistency. In order to obtain general results, suitable for several kinds of Pairwise Comparison Matrices proposed in literature, we focus on matrices defined over a general unifying framework, that is an Abelian linearly ordered group. In this context, firstly, we provide G-distance between Pairwise Comparison Matrices and G-decomposition of a Pairwise Comparison Matrix in its G-consistent and totally G-inconsistent components. Then, we show how a G-inconsistent Pairwise Comparison Matrix can be revised according to the associated G-consistent component; the revision process takes into account G-distance from the former in order to better represent decision maker's preferences.
机译:成对比较是比较替代品/标准的长期技术,并且它们的作用在现代决策方法的发展中得到了关键。由于一致性确保了合理的决策,因此在文献中提出了几种方法,用于修改成对比较矩阵以提高其一致性。为了获得一般结果,适用于文献中提出的几种成对比较矩阵,我们专注于在一般统一框架上定义的矩阵,即abelian线性有序组。在这方面,首先,我们在其G-Cnalinent和完全G-Convonstent组件中提供成对比较矩阵和G - 分解之间的G距离。然后,我们展示了如何根据关联的G-Cnaligate组件修改G-Nulist对比较矩阵;修订过程考虑到与前者的G距离,以便更好地代表决策者的偏好。

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