Motivated by the serious problem that hospitals in rural areas suffer from a shortage of residents, we study the Hospitals/Residents model in which hospitals are associated with lower quotas and the objective is to satisfy them as much as possible. When preference lists are strict, the number of residents assigned to each hospital is the same in any stable matching because of the well-known rural hospitals theorem; thus there is no room for algorithmic interventions. However, when ties are introduced to preference lists, this will no longer apply because the number of residents may vary over stable matchings. In this paper, we formulate an optimization problem to find a stable matching with the maximum total satisfaction ratio for lower quotas. We first investigate how the total satisfaction ratio varies over choices of stable matchings in four natural scenarios and provide the exact values of these maximum gaps. Subsequently, we propose a strategy-proof approximation algorithm for our problem; in one scenario it solves the problem optimally, and in the other three scenarios, which are NP-hard, it yields a better approximation factor than that of a naive tie-breaking method. Finally, we show inapproximability results for the above-mentioned three NP-hard scenarios.
翻译:由于农村地区医院存在居民短缺的严重问题,我们研究了医院/居民模式,医院/居民模式与低配额挂钩,目标是尽可能满足这些模式。如果优惠名单严格,由于众所周知的农村医院的理论原理,分配给每个医院的居民人数在任何稳定匹配中都是相同的;因此没有算法干预的空间。然而,在采用优惠名单时,这将不再适用,因为居民人数可能不同于稳定匹配。在本文中,我们提出了一个优化问题,以找到与低配额最高总满意率的稳定匹配。我们首先调查在四种自然假设中,总满意率相对于稳定匹配的选择有何不同,并提供了这些最大差距的确切价值。我们随后提出了针对我们的问题的防战略的近似算法;在一个假设中,它最妥善地解决了问题,而在另外三种假设中,由于NP-硬化,它产生比天真的断裂法更好的近似系数。最后,我们展示了上述三种PNP-硬假设的不适应性结果。