The ranking aggregation problem is gaining attention in different application fields due to its connection with decision making. One of the most famous ranking aggregation methods can be traced back to Kemeny in 1959. Unfortunately, the problem of determining the result of the aggregation proposed by Kemeny, known as Kemeny ranking as it minimizes the number of pairwise discrepancies from a set of rankings given by voters, has been proved to be NP-hard, which unfortunately prevents practitioners from using this method in most real-life problems. In this work, we introduce two exact algorithms for determining the Kemeny ranking. The best of these algorithms guarantees a reasonable search time up to 14 alternatives, showing an important reduction of the execution time in comparison to other algorithms found in the literature. Moreover, a dataset of profiles of rankings is provided and a study of additional aspects of the votes that may have impact on the execution time required to determine the winning ranking is also detailed.

排序聚合问题由于与决策的联系而受到不同应用领域的关注。最著名的排名聚合方法之一可以追溯到 1959 年的 Kemeny。不幸的是，确定 Kemeny 提出的聚合结果的问题，称为 Kemeny 排序，因为它最小化了给定的一组排名中的成对差异的数量被选民证明是 NP 难的，不幸的是，这阻止了从业者在大多数现实生活中的问题中使用这种方法。在这项工作中，我们介绍了两种用于确定 Kemeny 排名的精确算法。这些算法中最好的算法保证了合理的搜索时间，最多 14 个备选方案，与文献中发现的其他算法相比，执行时间显着减少。而且，