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Elementary Approximation Algorithms for Prize Collecting Steiner Tree Problems

机译:奖品斯坦纳树问题的基本近似算法

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This paper deals with approximation algorithms for the prize collecting generalized Steiner forest problem, defined as follows. The input is an undirected graph G = (V, E), a collection T = {T_1,..., T_k}, each a subset of V of size at least 2, a weight function w : E→R~+, and a penalty function p : T → R~+. The goal is to find a forest F that minimizes the cost of the edges of F plus the penalties paid for subsets T_i whose vertices are not all connected by F. Our main result is a combinatorial (3 - 4)-approximation for the prize collecting generalized Steiner forest problem, where n > 2 is the number of vertices in the graph. This obviously implies the same approximation for the special case called the prize collecting Steiner forest problem (all subsets T_i are of size 2). The approximation ratio we achieve is better than that of the best known combinatorial algorithm for this problem, which is the 3-approx-imation of Sharma, Swamy, and Williamson. Furthermore, our algorithm is obtained using an elegant application of the local ratio method and is much simpler and practical, since unlike the algorithm of Sharma et al., it does not use submodular function minimization. Our approach gives a (2 - 1/(n-1)-approximation for the prize collecting Steiner tree problem (all subsets T_i are of size 2 and there is some root vertex r that belongs to all of them). This latter algorithm is in fact the local ratio version of the primal-dual algorithm of Goemans and Williamson . Another special case of our main algorithm is Bar-Yehuda's local ratio (2 - 2-approximation for the generalized Steiner forest problem (all the penalties are infinity). Thus, an important contribution of this paper is in providing a natural generalization of the framework presented by Goemans and Williamson, and later by Bar-Yehuda.
机译:本文针对广义Steiner森林奖品收集问题的近似算法,定义如下。输入是无向图G =(V,E),集合T = {T_1,...,T_k},每个V的子集的大小至少为2,权重函数w为:E→R〜+,罚函数p​​:T→R〜+。目标是找到一个森林F,该森林最小化F的边沿成本以及对顶点不完全由F连接的子集T_i所支付的惩罚。我们的主要结果是对(3-4 / n)的组合近似奖品收集广义Steiner森林问题,其中n> 2是图中的顶点数。显然,这对于称为奖品收集斯坦纳森林问题的特殊情况(所有子集T_i的大小均为2)具有相同的近似值。对于此问题,我们获得的逼近率比最著名的组合算法要好,即Sharma,Swamy和Williamson的3逼近。此外,我们的算法是使用局部比率方法的优美应用而获得的,并且更加简单实用,因为与Sharma等人的算法不同,它不使用子模函数最小化。我们的方法给出了奖品收集斯坦纳树问题的(2-1 /(n-1)-近似值(所有子集T_i的大小均为2,并且有一些属于它们的根顶点r)。后一种算法是实际上是Goemans和Williamson的原始对偶算法的局部比率版本。我们主要算法的另一个特殊情况是Bar-Yehuda的局部比率(对于广义Steiner森林问题,近似为2-2 / n-逼近(所有惩罚都是无穷大) )因此,本文的重要贡献在于对Goemans和Williamson以及后来的Bar-Yehuda提出的框架进行了自然概括。

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