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Many-to-one Matchings with Lower Quotas: Algorithms and Complexity

机译:具有较低配额的多对一匹配:算法和复杂性

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We study a natural generalization of the maximum weight many-to-one matching problem. We are given an undirected bipartite graph G = (A∪P, E) with weights on the edges in E, and with lower and upper quotas on the vertices in P. We seek a maximum weight many-to-one matching satisfying two sets of constraints: vertices in A are incident to at most one matching edge, while vertices in P are either unmatched or they are incident to a number of matching edges between their lower and upper quota. This problem, which we call maximum weight many-to-one matching with lower and upper quotas (WMLQ), has applications to the assignment of students to projects within university courses, where there are constraints on the minimum and maximum numbers of students that must be assigned to each project. In this paper, we provide a comprehensive analysis of the complexity of WMLQ from the viewpoints of classic polynomial time algorithms, fixed-parameter tractability, as well as approximability. We draw the line between NP-hard and polynomially tractable instances in terms of degree and quota constraints and provide efficient algorithms to solve the tractable ones. We further show that the problem can be solved in polynomial time for instances with bounded treewidth; however, the corresponding runtime is exponential in the treewidth with the maximum upper quota u_(max) as basis, and we prove that this dependence is necessary unless FPT = W[1]. Finally, we also present an approximation algorithm for the general case with performance guarantee u_(max) + 1, which is asymptotically best possible unless P = NP.
机译:我们研究了最大重量的自然概括了多对一匹配问题。我们给出了一个过期的二分图G =(A∪P,e),在E中的边缘上的重量,并且在P的顶点上具有较低的和上配额。我们寻求最多的重量,满足两套的多对一匹配约束:A中的顶点是最多一个匹配边缘的,而P中的顶点是无与伦比的,或者它们是在其较低和上配额之间的多个匹配边缘。这个问题,我们称之为较低和上部配额(WMLQ)的最大重量匹配,具有向学生分配给大学课程的项目,其中有必要的最低和最大数量的限制分配给每个项目。在本文中,我们从经典多项式时间算法,固定参数扫护性以及近似性的观点来综合分析WMLQ的复杂性。我们在学位和配额约束方面绘制了NP-Hard和多项式贸易实例之间的线路,并提供有效的算法来解决易易手的算法。我们进一步表明,在具有有界树木宽度的情况下可以解决问题中的问题。但是,相应的运行时在树宽中是指数级的,其具有最大的上部配额U_(MAX)作为基础,并且我们证明除非FPT = W [1],否则必须依赖这种依赖性。最后,除非p = np,否则我们还向常见情况下呈现近似估计算法,其性能保证u_(max)+ 1是渐近的最佳状态。

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