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Improved Decremental Algorithms for Maintaining Transitive Closure and Allpairs Shortest Paths

机译:维持传递闭包和所有对最短路径的改进的减量算法

摘要

We present improved algorithms for maintaining transitive closure and all-pairs shortest paths/distances in a digraph under deletion of edges.(MATH) For the problem of transitive closure, the previous best known algorithms, for achieving O(1) query time, require O(min(m, rac{n^3}{m}))$ amortized update time, implying an upper bound of O(n^{rac{3}{2}})$ on update time per edge-deletion. We present an algorithm that achieves $O(1)$ query time and O(n log^2n + rac{n^2}{sqrt{m}}{sqrt{log n}})$ update time per edge-deletion, thus improving the upper bound to O(n^{rac{4}{3}}sqrt[3]{log n})$.(MATH) For the problem of maintaining all-pairs shortest distances in unweighted digraph under deletion of edges, we present an algorithm that requires O(rac{n^3}{m} log^2 n)$ amortized update time and answers a distance query in O(1) time. This improves the previous best known update bound by a factor of log n. For maintaining all-pairs shortest paths, we present an algorithm that achieves O(min(n^{rac{3}{2}} sqrt{log n}, rac{n^3}{m} log ^2n))$ amortized update time and reports a shortest path in optimal time (proportional to the length of the path). For the latter problem we improve the worst amortized update time bound by a factor of O(sqrt{rac{n}{log n}})$.(MATH) We also present the first decremental algorithm for maintaining all-pairs (1+&egr;) approximate shortest paths/distances, for any &egr; > 0, that achieves a sub-quadratic update time of O(n log2n + rac{n^2}{sqrt{epsilon m}}sqrt{log n})$ and optimal query time.Our algorithms are randomized and have one-sided error for query (with probability O(1/nc) for any constant c).
机译:我们提出了一种改进的算法,用于在删除边的情况下保持有向闭合和全对最短路径/距离在有向图中。(MATH)对于有向闭合的问题,用于实现O(1)查询时间的先前最著名的算法需要O( min(m, frac {n ^ 3} {m}))$分期更新时间,这意味着每个边缘的更新时间上限为O(n ^ { frac {3} {2}})$ -删除。我们提出了一种实现$ O(1)$查询时间和O(n log ^ 2n + frac {n ^ 2} { sqrt {m}} { sqrt { log n}})$更新时间的算法每个边缘删除,从而改善了O(n ^ { frac {4} {3}} sqrt [3] { log n})$。(MATH)的问题,因为所有对都保持最短删除边后未加权有向图的距离,我们提出了一种算法,该算法需要O( frac {n ^ 3} {m} log ^ 2 n)$摊销更新时间,并以O(1)时间回答距离查询。这改善了先前最著名的更新,其限制为log n。为了维持所有对的最短路径,我们提出了一种算法,可以实现O( min(n ^ { frac {3} {2}} sqrt { log n}, frac {n ^ 3} {m} log ^ 2n))$摊销更新时间,并报告最佳时间内的最短路径(与路径长度成比例)。对于后一个问题,我们改进了最坏的摊销更新时间,范围为O( sqrt { frac {n} { log n}})$。(MATH)我们还提出了第一种用于维持所有对的递减算法。 (1 +&egr;)近似于任何&egr;的最短路径/距离> 0,可实现二次更新时间O(n log2n + frac {n ^ 2} { sqrt { epsilon m}} sqrt { log n})$和最佳查询时间。我们的算法是随机且具有单向错误查询(对于任何常数c,概率为O(1 / nc))。

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