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Constant-Time Approximation Algorithms for the Optimum Branching Problem on Sparse Graphs

机译:稀疏图中最佳分支问题的恒定时间近似算法

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We propose constant-time algorithms for approximating the weight of the maximum weight branching in the general graph model. A directed graph is called a branching if it is acyclic and each vertex has at most one incoming edge. An edge-weighted digraph G, in which weights are given in real values in [0,1], of average degree d is given as an oracle access, and we are allowed to ask degrees and incoming edges for every vertex through the oracle. Then, with high probability, our algorithm estimates the weight of the maximum weight branching in G with an absolute error of at most εn with query complexity O(d/ε~3), where n is the number of vertices. We also show a lower bound of ?(d/ε~2). Additionally, our algorithm can be modified to run with query complexity O(1/ε~4) for unweighted digraphs, i.e., it runs in time independent of the input size even for digraphs with ?(n~2) edges. In contrast, we show that it requires ?(n) queries to approximate the weight of the minimum (or maximum) spanning arborescence in a weighted digraph.
机译:我们提出了恒定时间算法,用于近似概述一般图模型中的最大重量分支的重量。如果它是acyclic,则指向图称为分支,并且每个顶点在大多数输入边缘处具有。边缘加权的DIGRAPH G,其中在[0,1]中的实际值中给出了平均d程度D的重量,作为ORACLE访问,我们被允许以ORACLE向每个顶点询问度数和传入边缘。然后,以高概率,我们的算法估计的最大重量的G中分支至多εN与查询复杂度为O的绝对误差(d /ε〜3),其中n的重量的顶点的数量。我们还显示出较低的界限(D /ε〜2)。另外,可以修改我们的算法以运行查询复杂性O(1 /ε〜4),用于未加权的数字,即,即使对于具有?(n〜2)边缘的数字,它也与输入大小无关。相反,我们表明它需要?(n)查询,以近似加权数字中的跨越跨越植树的最小(或最大)的重量。

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