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Improved Approximation Algorithms for the Min-Max Tree Cover and Bounded Tree Cover Problems

机译:最小-最大树覆盖问题和有界树覆盖问题的改进的近似算法

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In this paper we provide improved approximation algorithms for the Min-Max Tree Cover and Bounded Tree Cover problems. Given a graph G = (V, E) with weights w : E → N~+, a set T_1,T_2,...,T_k of subtrees of G is called a tree cover of G if V = ∪_(i=1)~k V(T_i). In the Min Max k-tree Cover problem we are given graph G and a positive integer k and the goal is to find a tree cover with k trees, such that the weight of the largest tree in the cover is minimized. We present a 3-approximation algorithm for this improving the two different approximation algorithms presented in [1,5] with ratio 4. The problem is known to have an APX-hardness lower bound of 3/2 [12]. In the Bounded Tree Cover problem we are given graph G and a bound λ and the goal is to find a tree cover with minimum number of trees such that each tree has weight at most λ. We present a 2.5-approximation algorithm for this, improving the 3-approximation bound in [1].
机译:在本文中,我们针对最小-最大树覆盖和有界树覆盖问题提供了改进的近似算法。给定一个权重为w:E→N〜+的图G =(V,E),如果V =∪_(i = I,则将G的子树的集合T_1,T_2,...,T_k称为G的树覆盖。 1)〜k V(T_i)。在最小最大k树覆盖问题中,我们得到了图G和一个正整数k,目标是找到一个包含k棵树的树覆盖,以使覆盖中最大树的权重最小。我们提出了一种3-近似算法,用于以比率4改进[1,5]中介绍的两种不同的近似算法。已知该问题的APX硬度下限为3/2 [12]。在有界树覆盖问题中,我们得到了图G和一个有界的λ,目标是找到树木数量最少的树,使得每棵树的权重最大为λ。为此,我们提出了一种2.5近似算法,改进了[1]中的3近似界限。

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