Abstract

In the problem of collective choice, an algorithm is proposed for constructing an optimal aggregate ranking that is closest to all individual strict rankings in the sense of the Kemeny median. The application of the branch-and-bound method allows problems of large dimensions to be solved and can also be used in the case when individual preferences are arbitrary binary relations.

中文翻译：

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分枝定界法合并单项排名

摘要

在集体选择问题中，提出了一种算法，用于构建最接近Kemeny中位数意义上的所有个体严格排名的最优聚合排名。分支定界法的应用可以解决大维度的问题，也可以用于个体偏好为任意二元关系的情况。