We consider a matching problem in a bipartite graph $G=(A\cup B,E)$ where each node in $A$ is an agent having preferences in partial order over her neighbors, while nodes in $B$ are objects with no preferences. The size of our matching is more important than node preferences; thus, we are interested in maximum matchings only. Any pair of maximum matchings in $G$ (equivalently, perfect matchings or assignments) can be compared by holding a head-to-head election between them where agents are voters. The goal is to compute an assignment $M$ such that there is no better or "more popular" assignment. This is the popular assignment problem and it generalizes the well-studied popular matching problem. Popular assignments need not always exist. We show a polynomial-time algorithm that decides if the given instance admits one or not, and computes one, if so. In instances with no popular assignment, we consider the problem of finding an almost popular assignment, i.e., an assignment with minimum unpopularity margin. We show an $O^*(|E|^k)$ time algorithm for deciding if there exists an assignment with unpopularity margin at most $k$. We show that this algorithm is essentially optimal by proving that the problem is $\mathsf{W}_l[1]$-hard with parameter $k$. We also consider the minimum-cost popular assignment problem when there are edge costs, and show its $\mathsf{NP}$-hardness even when all edge costs are in $\{0,1\}$ and agents have strict preferences. By contrast, we propose a polynomial-time algorithm to the problem of deciding if there exists a popular assignment with a given set of forced/forbidden edges (this tractability holds even for partially ordered preferences). Our algorithms are combinatorial and based on LP duality. They search for an appropriate witness or dual certificate, and when a certificate cannot be found, we prove that the desired assignment does not exist in $G$.
翻译:在双部分方程式$G=(A\cup B, {E)中,我们考虑匹配问题。在双部分方程式$G=(A\cup B, {E)中,每个A$节点都是一个对其邻居有部分偏好的代理商,而$B$的节点则是没有偏好的对象。我们的匹配规模比节点偏好;因此,我们只对最大匹配感兴趣。任何一对最大匹配以$G$(等值、完美匹配或任务),都可以通过在它们之间举行头对头选举来比较,如果代理商是选民的话。目标是计算一个任务单位$M$,这样的话,没有更好的或“更受欢迎的”任务。这是流行的任务问题,而且它一般化的流行匹配问题。我们展示了一个多位数时间算算法,决定某个事件是否承认一个或不完全正确,如果我们以美元值的运算值表示一个最优的运算值,那么当我们发现一个不受欢迎的任务时,我们就会发现一个相当的运价比值, 当我们发现一个最低的运算时, 当我们以最优的运算时, 美元的运算时, 当我们以美元表示一个最优的运算算算时, 美元为一个最优值的运算时, 。