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An application of incomplete pairwise comparison matrices for ranking top tennis players

机译:不完全配对比较矩阵在顶级网球运动员排名中的应用

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摘要

Pairwise comparison is an important tool in multi-attribute decision making. Pairwise comparison matrices (PCM) have been applied for ranking criteria and for scoring alternatives according to a given criterion. Our paper presents a special application of incomplete PCMs: ranking of professional tennis players based on their results against each other. The selected 25 players have been on the top of the ATP rankings for a shorter or longer period in the last 40 years. Some of them have never met on the court. One of the aims of the paper is to provide ranking of the selected players, however, the analysis of incomplete pairwise comparison matrices is also in the focus. The eigenvector method and the logarithmic least squares method were used to calculate weights from incomplete PCMs. In our results the top three players of four decades were Nadal, Federer and Sampras. Some questions have been raised on the properties of incomplete PCMs and remains open for further investigation. (C) 2015 Elsevier B.V. and Association of European Operational Research Societies (EURO) within the International Federation of Operational Research Societies (IFORS). All rights reserved.
机译:成对比较是多属性决策中的重要工具。成对比较矩阵(PCM)已应用于排名标准和根据给定标准对备选方案评分。我们的论文提出了不完全PCM的特殊应用:基于职业网球选手彼此之间的排名来对其排名。在过去的40年中,短短或更长的时间,入选的25名球员一直在ATP排名中名列前茅。他们中有些人从未在球场上见过面。本文的目的之一是提供所选参与者的排名,但是,不完整的成对比较矩阵的分析也是重点。本征向量法和对数最小二乘法被用来计算不完全PCM的权重。在我们的成绩中,四十年来排名前三的球员是纳达尔,费德勒和桑普拉斯。关于不完全PCM的性质已经提出了一些问题,这些问题尚待进一步研究。 (C)2015年Elsevier B.V.和国际运营研究学会联合会(IFORS)中的欧洲运营研究学会协会(EURO)。版权所有。

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