Abstract

There are many priority deriving methods for pairwise comparison (PC) matrices. It is known that when these matrices are consistent all these methods result in the same priority vector. However, when they are inconsistent, the results may vary. The presented work formulates an estimation of the difference between priority vectors in the two most popular ranking methods: the eigenvalue method and the geometric mean method. The estimation provided refers to the inconsistency of the PC matrix. Theoretical considerations are accompanied by Monte Carlo experiments showing the discrepancy between the values of both methods.

中文翻译：

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两两比较法中排序向量的相似度

摘要

成对比较 (PC) 矩阵有许多优先级推导方法。众所周知，当这些矩阵一致时，所有这些方法都会产生相同的优先级向量。但是，当它们不一致时，结果可能会有所不同。所提出的工作制定了两种最流行的排名方法中优先级向量之间差异的估计：特征值方法和几何平均方法。提供的估计是指 PC 矩阵的不一致性。理论考虑伴随着蒙特卡罗实验，表明两种方法的值之间存在差异。