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Faster Computation of the Maximum Dissociation Set and Minimum 3-Path Vertex Cover in Graphs

机译:图形中最大离解集和最小3路径顶点覆盖的更快计算

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A dissociation set in a graph G = (V, E) is a vertex subset D such that the subgraph G[D] induced on D has vertex degree at most 1. A 3-path vertex cover in a graph is a vertex subset C such that every path of three vertices contains at least one vertex from C. Clearly, a vertex set D is a dissociation set if and only if V D is a 3-path vertex cover. There are many applications for dissociation sets and 3-path vertex covers. However, it is NP-hard to compute a dissociation set of maximum size or a 3-path vertex cover of minimum size in graphs. Several exact algorithms have been proposed for these two problems and they can be solved in O~*(1.4658~n) time in n-vertex graphs. In this paper, we reveal some interesting structural properties of the two problems, which allow us to solve them in O~*(1.4656~n) time and polynomial space or O~*(1.3659~n) time and exponential space.
机译:图G =(V,E)中的解离集是顶点子集D,因此在D上诱导的子图G [D]的顶点度最大为1。图中的3路径顶点覆盖是顶点子集C这样,三个顶点的每个路径都包含至少一个来自C的顶点。显然,当且仅当V \ D为3路径顶点覆盖时,顶点集D才是解离集合。离解集和3路径顶点覆盖有许多应用程序。但是,要计算图中最大尺寸的解离集或最小尺寸的3路径顶点覆盖率很困难。已经针对这两个问题提出了几种精确的算法,它们可以在n-顶点图中的O〜*(1.4658〜n)时间内求解。在本文中,我们揭示了这两个问题的一些有趣的结构性质,这使我们能够在O〜*(1.4656〜n)时间和多项式空间或O〜*(1.3659〜n)时间和指数空间中求解它们。

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