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Consistency and consensus improving methods for pairwise comparison matrices based on Abelian linearly ordered group

机译:基于Abelian线性有序群的成对比较矩阵的一致性和一致性改进方法

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摘要

The aim of a valued pairwise comparison matrix is to derive the priority structure over a set of criteria (or alternatives) in decision making. The consistency and consensus of a pairwise comparison matrix should be measured and improved to avoid a misleading priority structure. The basic entries of a pairwise comparison matrix can be described in different forms; hence, different consistency and consensus methods should be developed for different types of matrices. To provide a general framework, the pairwise comparison matrix based on Abelian linearly ordered group is first introduced. A consistency index is defined by constructing the nearest consistent pairwise comparison matrix from an inconsistent one, and two consistency improving methods are introduced. A group pairwise comparison matrix is derived, a consensus index of individual pairwise comparison matrices is defined and two consensus improving methods are developed by introducing a general aggregation operator based on Abelian linearly ordered group. The proposed consistency and consensus methods are convergent and can provide a general framework for existing methods.
机译:有价值的成对比较矩阵的目的是在决策过程中推导一组标准(或替代方法)的优先级结构。应该测量和改进成对比较矩阵的一致性和共识,以避免产生误导性的优先级结构。成对比较矩阵的基本条目可以用不同的形式描述。因此,应针对不同类型的矩阵开发不同的一致性和共识方法。为了提供一个通用的框架,首先引入了基于阿贝尔线性排序群的成对比较矩阵。通过从一个不一致的矩阵构造最近的一致的成对比较矩阵来定义一致性指数,并介绍了两种一致性改进方法。推导了一个成对的成对比较矩阵,定义了各个成对的比较矩阵的共识指数,并通过引入基于Abelian线性有序群的一般聚合算子,开发了两种共识改进方法。所提出的一致性和共识方法是趋同的,可以为现有方法提供一个通用框架。

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