配对比较问题中的极值

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摘要

目标。对基于专家配对比较结果的方案评价问题进行了分析。这项任务的重要性和相关性是由于它在各种领域的大量应用,无论是在技术和自然科学还是在人文科学,从建筑到政治。在这种情况下,经常出现如何根据专家评价计算客观评级向量的问题。用数学公式表示,寻找客观评价向量的问题可以简化为用一致矩阵近似成对比较的矩阵。采用解析分析和高等代数方法。对于一些特殊情况,给出了数值计算结果。证明了对数欧几里得度量中总有一个唯一且一致的矩阵最优逼近给定的逆对称矩阵的定理。此外,还给出了计算这种一致矩阵的推导公式。对于小维度,考虑了一些例子,允许根据导出公式获得的结果与其他已知的寻找一致矩阵的方法的结果进行比较,即计算特征向量并最小化对数-切比雪夫度量的差异。结果表明,这些方法在第3维度上的结果是一致的,而在第4维度上的结果是不同的。本文的研究结果使我们能够在专家评价数据的基础上计算客观评分向量。在只有根据专家评价才能得出结论和提出建议的情况下,这种方法可用于战略规划。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Extremum in the problem of paired comparisons
Objectives. An analysis of the problem of evaluating alternatives based on the results of expert paired comparisons is presented. The importance and relevance of this task is due to its numerous applications in a variety of fields, whether in the technical and natural sciences or in the humanities, ranging from construction to politics. In such contexts, the problem frequently arises concerning how to calculate an objective ratings vector based on expert evaluations. In terms of a mathematical formulation, the problem of finding the vector of objective ratings can be reduced to approximating the matrices of paired comparisons by consistent matrices.Methods. Analytical analysis and higher algebra methods are used. For some special cases, the results of numerical calculations are given.Results. The theorem stating that there is always a unique and consistent matrix that optimally approximates a given inversely symmetric matrix in a log-Euclidean metric is proven. In addition, derived formulas for calculating such a consistent matrix are presented. For small dimensions, examples are considered that allow the results obtained according to the derived formula to be compared with results for other known methods of finding a consistent matrix, i.e., for calculating the eigenvector and minimizing the discrepancy in the log-Chebyshev metric. It is proven that all these methods lead to the same result in dimension 3, while in dimension 4 all results are already different.Conclusions. The results obtained in the paper allow us to calculate the vector of objective ratings based on expert evaluation data. This method can be used in strategic planning in cases where conclusions and recommendations are possible only on the basis of expert evaluations.
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