全动态匹配的新确定性近似算法

Sayan Bhattacharya, M. Henzinger, Danupon Nanongkai
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引用次数: 94

摘要

针对最大匹配问题,提出了两种确定性动态算法。(1)用O(poly(logn, 1/ n))更新时间在一般图中保持(2+ n)-近似最大匹配的算法。(2)对于二部图中每一个足够大的常数正整数K,其最大匹配值与更新时间O(n2/K)保持αK近似,其中1≤αK < 2是由K的值决定的常数。结果(1)是第一个能够在多对数更新时间保持O(logn)-近似最大匹配的确定性算法,改进了Onak等人[STOC 2010]的重要结果。其近似保证几乎与最佳随机化多对数更新时间算法的保证相匹配[Baswana等]。foc 2011]。结果(2)在二部图上以任意小的多项式更新时间实现了一个优于二的近似。以前,此问题的最佳更新时间为O(m1/4) [Bernstein等人]。ICALP 2015],其中m为图中当前边的个数。
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New deterministic approximation algorithms for fully dynamic matching
We present two deterministic dynamic algorithms for the maximum matching problem. (1) An algorithm that maintains a (2+є)-approximate maximum matching in general graphs with O(poly(logn, 1/є)) update time. (2) An algorithm that maintains an αK approximation of the value of the maximum matching with O(n2/K) update time in bipartite graphs, for every sufficiently large constant positive integer K. Here, 1≤ αK < 2 is a constant determined by the value of K. Result (1) is the first deterministic algorithm that can maintain an o(logn)-approximate maximum matching with polylogarithmic update time, improving the seminal result of Onak et al. [STOC 2010]. Its approximation guarantee almost matches the guarantee of the best randomized polylogarithmic update time algorithm [Baswana et al. FOCS 2011]. Result (2) achieves a better-than-two approximation with arbitrarily small polynomial update time on bipartite graphs. Previously the best update time for this problem was O(m1/4) [Bernstein et al. ICALP 2015], where m is the current number of edges in the graph.
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