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Faster approximation algorithms for the minimum latency problem

机译:最小延迟问题的更快近似算法

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In this paper, we give a 9.28-approximation algorithm for the minimum latency problem that uses only O(n log n) calls to the prize-collecting Steiner tree (PCST) subroutine of Goemans and Williamson. A previous algorithm of Goemans and Kleinberg for the minimum latency problem requires an approximation algorithm for the k-MST problem which is called as a black box. Their algorithm can achieve a performance guarantee of 10.77 while making O(n2 log n) PCST calls (via a k-MST algorithm of Garg), or a performance guarantee of 7.18 + ε while using nO(1/ε) PCST calls (via a k-MST algorithm of Arora and Karakostas). In order to match our approximation ratio (i.e. setting ε = 2.10), the latter version requires O(n5 log2 n) PCST calls, so our running time bound is faster by a factor of Θ(n4 log n). Since PCST can be implemented to run in O(n2) time, the overall running time of our algorithm is O(n3 log n).The basic idea for our improvement is that we do not treat the k-MST algorithm as a black box. Thus we are able to take advantage of some situations in which the PCST subroutine delivers a k-MST with an improved performance guarantee.
机译:本文针对最小延迟问题给出了9.28近似算法,该算法仅使用 O n log n )调用奖品收集Goemans和Williamson的Steiner树(PCST)子例程。 Goemans和Kleinberg的用于最小等待时间问题的先前算法需要 k -MST问题的近似算法,称为黑盒。他们的算法在进行 O n 2 log n )PCST调用时可以实现10.77的性能保证。 ( k -MST算法),或使用 n O (1 /ε)时的性能保证为7.18 +ε PCST调用(通过Arora和Karakostas的 k -MST算法)。为了匹配我们的近似比率(即设置ε= 2.10),后一个版本需要 O n 5 log 2 < / SUP> n )PCST调用,因此我们的运行时间缩短了Θ( n 4 log n < / I>)。由于PCST可以实现为在 O n 2 )时间内运行,因此我们算法的总运行时间为 O n 3 log n )。改进的基本思路是不处理 k -MST算法作为黑匣子。因此,我们可以利用PCST子例程提供具有改进性能保证的 k -MST的某些情况。

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