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A Weighted Approach to the Maximum Cardinality Bipartite Matching Problem with Applications in Geometric Settings

机译:在几何设置中的应用中的最大基数双链匹配问题的加权方法

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We present a weighted approach to compute a maximum cardinality matching in an arbitrary bipartite graph. Our main result is a new algorithm that takes as input a weighted bipartite graph G(A cup B,E) with edge weights of 0 or 1. Let w <= n be an upper bound on the weight of any matching in G. Consider the subgraph induced by all the edges of G with a weight 0. Suppose every connected component in this subgraph has O(r) vertices and O(mr/n) edges. We present an algorithm to compute a maximum cardinality matching in G in O~(m(sqrt{w} + sqrt{r} + wr/n)) time. When all the edge weights are 1 (symmetrically when all weights are 0), our algorithm will be identical to the well-known Hopcroft-Karp (HK) algorithm, which runs in O(m sqrt{n}) time. However, if we can carefully assign weights of 0 and 1 on its edges such that both w and r are sub-linear in n and wr=O(n^{gamma}) for gamma < 3/2, then we can compute maximum cardinality matching in G in o(m sqrt{n}) time. Using our algorithm, we obtain a new O~(n^{4/3}/epsilon^4) time algorithm to compute an epsilon-approximate bottleneck matching of A,B subsetR^2 and an 1/(epsilon^{O(d)}}n^{1+(d-1)/(2d-1)}) poly log n time algorithm for computing epsilon-approximate bottleneck matching in d-dimensions. All previous algorithms take Omega(n^{3/2}) time. Given any graph G(A cup B,E) that has an easily computable balanced vertex separator for every subgraph G'(V',E') of size |V'|^{delta}, for delta in [1/2,1), we can apply our algorithm to compute a maximum matching in O~(mn^{delta/1+delta}) time improving upon the O(m sqrt{n}) time taken by the HK-Algorithm.
机译:我们提出了一种加权方法来计算任意二分钟的最大基数匹配。我们的主要结果是一种新的算法,它用作0或1.边缘重量的加权二分图G(A CUP B,E)的输入,让W <= N是G.考虑任何匹配的重量的上限由G的所有边缘引起的子图,其重量为0。在该子图中的每个连接的组件都有O(R)顶点和O(MR / N)边缘。我们介绍了一种算法来计算在o〜(m(sqrt {w + sqrt {r} + wr / n))中的g中的最大基数匹配。当所有边缘重量为1(当所有重量为0时对称)时,我们的算法将与众所周知的HopCroft-KARP(HK)算法相同,该算法在O(M SQRT {N})时间内运行。但是,如果我们可以仔细地将0和1的重量分配在其边缘上,使得w和r在n和wr = o(n ^ {gamma})中是伽马<3/2的子线性,然后我们可以计算最大值在o(m sqrt {n})时的基数匹配。使用我们的算法,我们获得了一个新的O〜(n ^ {4/3} / epsilon ^ 4)时间算法,用于计算A,B子集^ 2和1 /(epsilon ^ {o()的epsilon - 近似瓶颈匹配。 d)}} n ^ {1+(d-1)/(2d-1)})用于计算D-尺寸中匹配的epsilon近似瓶颈的聚日志n时间算法。以前的所有算法都采用Omega(n ^ {3/2})时间。给定任何具有易于计算的平衡顶点分离器的图表G(a cup b,e),每个子图g'(v',e')的大小| v'| ^ {delta},在[1/2中的delta中, 1),我们可以应用算法来计算由HK算法采取的O(Mn ^ {delta / 1 + delta})时间内的最大匹配时间,从而提高O(m sqrt {n})时间。

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