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Labeled Search Trees and Amortized Analysis: Improved Upper Bounds for NP-Hard Problems

机译:标记的搜索树和摊销分析:NP-硬问题的改进上限

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A sequence of exact algorithms to solve the VERTEX COVER and MAXIMUM INDEPENDENT SET problems have been proposed recently in the literature. All these algorithms appeal to a very conservative analysis that considers the size of the search tree, under a worst-case scenario, to derive an upper bound on the running time of the algorithm. In this paper we propose a different approach to analyze the size of the search tree. We use amortized analysis to show how simple algorithms, if analyzed properly, may perform much better than the upper bounds on their running time derived by considering only a worst-case scenario. This approach allows us to present a simple algorithm of running time O(1.194~k+n) for the parameterized VERTEX COVER problem on degree-3 graphs, and a simple algorithm of running time O(1.1254~n) for the MAXIMUM INDEPENDENT SET problem on degree-3 graphs. Both algorithms improve the previous best algorithms for the problems.
机译:最近在文献中提出了一系列精确的算法来解决VERTEX覆盖和最大独立集问题。所有这些算法都吸引了一个非常保守的分析,该分析在最坏的情况下考虑了搜索树的大小,以得出算法运行时间的上限。在本文中,我们提出了一种不同的方法来分析搜索树的大小。我们使用摊销分析来显示简单算法(如果经过正确分析)与仅考虑最坏情况的情况下得出的运行时间上限相比,其性能会好得多。这种方法使我们能够为度数为3的图呈现参数化VERTEX COVER问题的运行时间O(1.194〜k + n)的简单算法,以及针对最大独立集的运行时间O(1.1254〜n)的简单算法3级图上的问题。两种算法都改进了先前针对该问题的最佳算法。

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