Popular Matchings with Multiple Partners

F. Brandl, T. Kavitha
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引用次数: 14

Abstract

Our input is a bipartite graph $G = (A \cup B,E)$ where each vertex in $A \cup B$ has a preference list strictly ranking its neighbors. The vertices in $A$ and in $B$ are called students and courses, respectively. Each student $a$ seeks to be matched to $\mathsf{cap}(a) \ge 1$ courses while each course $b$ seeks $\mathsf{cap}(b) \ge 1$ many students to be matched to it. The Gale-Shapley algorithm computes a pairwise-stable matching (one with no blocking edge) in $G$ in linear time. We consider the problem of computing a popular matching in $G$ -- a matching $M$ is popular if $M$ cannot lose an election to any matching where vertices cast votes for one matching versus another. Our main contribution is to show that a max-size popular matching in $G$ can be computed by the 2-level Gale-Shapley algorithm in linear time. This is an extension of the classical Gale-Shapley algorithm and we prove its correctness via linear programming.
与多个合作伙伴的流行匹配
我们的输入是一个二部图$G = (A \cup B,E)$,其中$A \cup B$中的每个顶点都有一个对其邻居严格排序的偏好列表。$A$和$B$中的顶点分别称为学生和课程。每个学生$a$寻求与$\mathsf{cap}(a) \ge 1$课程相匹配,而每个课程$b$寻求$\mathsf{cap}(b) \ge 1$许多学生与其相匹配。Gale-Shapley算法在线性时间内计算$G$的成对稳定匹配(无阻塞边缘)。我们考虑在$G$中计算流行匹配的问题——如果$M$不会输掉任何匹配的选举,那么匹配$M$就是流行的,其中顶点为一个匹配投票而不是另一个匹配。我们的主要贡献是表明$G$中的最大尺寸流行匹配可以通过线性时间内的2级Gale-Shapley算法计算。这是对经典Gale-Shapley算法的推广,并通过线性规划证明了其正确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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