A Class of Dissimilarity Semimetrics for Preference Relations

IF 1.4 3区 数学 Q2 MATHEMATICS, APPLIED
Hiroki Nishimura, Efe A. Ok
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引用次数: 3

Abstract

We propose a class of semimetrics for acyclic preference relations, any one of which is an alternative to the classical Kemeny-Snell-Bogart metric. These semimetrics are based solely on the implications of preferences for choice behavior and thus appear more suitable in economic contexts and choice experiments. We obtain a fairly simple axiomatic characterization for the class we propose. The apparently most important member of this class, which we dub the “top-difference semimetric,” is characterized separately. We also obtain alternative formulae for it and, relative to this particular metric, compute the diameter of the space of complete and transitive preferences, as well as the best transitive extension of a given acyclic preference relation. Supplemental Material: The e-companion is available at https://doi.org/10.1287/moor.2022.0351 .
一类偏好关系的非相似半度量
我们提出了一类非循环偏好关系的半度量,其中任何一类都是经典Kemeny-Snell-Bogart度量的替代。这些半度量仅基于选择行为偏好的含义,因此似乎更适合于经济背景和选择实验。对于我们提出的类,我们得到了一个相当简单的公理化表征。显然,这类中最重要的成员,我们称之为“顶差半度量”,是单独描述的。我们还得到了它的替代公式,并相对于这个特定的度量,计算了完全和传递偏好空间的直径,以及给定的非循环偏好关系的最佳传递扩展。补充材料:电子伴侣可在https://doi.org/10.1287/moor.2022.0351上获得。
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来源期刊
Mathematics of Operations Research
Mathematics of Operations Research 管理科学-应用数学
CiteScore
3.40
自引率
5.90%
发文量
178
审稿时长
15.0 months
期刊介绍: Mathematics of Operations Research is an international journal of the Institute for Operations Research and the Management Sciences (INFORMS). The journal invites articles concerned with the mathematical and computational foundations in the areas of continuous, discrete, and stochastic optimization; mathematical programming; dynamic programming; stochastic processes; stochastic models; simulation methodology; control and adaptation; networks; game theory; and decision theory. Also sought are contributions to learning theory and machine learning that have special relevance to decision making, operations research, and management science. The emphasis is on originality, quality, and importance; correctness alone is not sufficient. Significant developments in operations research and management science not having substantial mathematical interest should be directed to other journals such as Management Science or Operations Research.
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