首页> 外文会议>Foundations of Computer Science, 1996. Proceedings., 37th Annual Symposium on >An 8-approximation algorithm for the subset feedback vertex set problem
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An 8-approximation algorithm for the subset feedback vertex set problem

机译:子集反馈顶点集问题的8近似算法

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We present an 8-approximation algorithm for the problem of finding a minimum weight subset feedback vertex set. The input in this problem consists of an undirected graph G=(V,E) with vertex weights w(v) and a subset of vertices S called special vertices. A cycle is called interesting if it contains at least one special vertex. A subset of vertices is called a subset feedback vertex set with respect to S if it intersects every interesting cycle The goal is to find a minimum weight subset feedback vertex set. The best pervious algorithm for the general case provided only a logarithmic approximation factor. The minimum weight subset feedback vertex set problem generalizes two NP-Complete problems: the minimum weight feedback vertex set problem in undirected graphs and the minimum weight multiway vertex cut problem. The main tool that we use in our algorithm and its analysis is a new version of multi-commodity flow which we call relaxed multi-commodity flow. Relaxed multi-commodity flow is a hybrid of multi-commodity flow and multi-terminal flow.
机译:对于提出最小权重子集反馈顶点集的问题,我们提出了一种8近似算法。此问题中的输入包括一个顶点权重为w(v)的无向图G =(V,E)和一个称为特殊顶点的顶点S的子集。如果一个循环至少包含一个特殊的顶点,则称为“有趣”。如果每个子周期相交,则顶点的子集相对于S称为子集反馈顶点集。目标是找到最小权重子集反馈顶点集。对于一般情况,最佳的透水算法仅提供对数逼近因子。最小权重子集反馈顶点集问题概括了两个NP-Complete问题:无向图中的最小权重反馈顶点集问题和最小权重多向顶点割问题。我们在算法及其分析中使用的主要工具是多商品流的新版本,我们称其为宽松的多商品流。宽松的多商品流是多商品流和多终端流的混合体。

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