We study a generalization of the classical stable matching problem that allows for cardinal preferences (as opposed to ordinal) and fractional matchings (as opposed to integral). After observing that, in this cardinal setting, stable fractional matchings can have much higher social welfare than stable integral ones, our goal is to understand the computational complexity of finding an optimal (i.e., welfare-maximizing) or nearly-optimal stable fractional matching. We present simple approximation algorithms for this problem with weak welfare guarantees and, rather unexpectedly, we furthermore show that achieving better approximations is hard. This computational hardness persists even for approximate stability. To the best of our knowledge, these are the first computational complexity results for stable fractional matchings. En route to these results, we provide a number of structural observations.
翻译:我们研究传统稳定匹配问题的一般化,从而允许基本偏好(而不是正统)和分数匹配(而不是整体化 ) 。 我们发现,在这个基本环境里,稳定的分数匹配可以带来比稳定的整体匹配更好的社会福利,我们的目标是了解找到最佳(即福利最大化)或近乎最佳稳定分数匹配的计算复杂性。我们提出简单的近似算法来解决这个问题,而福利保障却很弱,而且出乎意料地,我们进一步表明,实现更好的近似很难。这种计算硬性即使为了近似稳定,也持续存在。据我们所知,这是稳定分数匹配的第一个计算复杂结果。在通往这些结果的道路上,我们提供了一些结构性的观察。