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Elementary approximation algorithms for prize collecting Steiner tree problems

机译:用于奖品收集斯坦纳树问题的基本近似算法

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摘要

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 (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 algorithm is obtained by applying the local ratio method, and is much simpler than the best known combinatorial algorithm for this problem. 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 [M.X. Goemans, D.P. Williamson, A general approximation technique for constrained forest problems, SIAM Journal on Computing 24 (2) (April 1995) 296-317]. 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) [R. Bar-Yehuda, One for the price of two: a unified approach for approximating covering problems, Algorithmica 27 (2) (June 2000) 131-144]. 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:E→R〜+,罚函数p​​:T→R〜+。我们的目标是找到一个森林F,该森林使F的边缘成本以及对顶点不完全由F连接的子集T_i所支付的罚款最小化。我们的主要结果是奖金的(3-4-/ n)逼近收集广义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。近似算法是通过应用局部比率方法获得的,并且比针对该问题的最佳已知组合算法要简单得多。我们的方法给出了奖品收集斯坦纳树问题的(2-1 /(n-1))逼近度(所有子集T_i的大小为2,并且有一些根顶点r属于它们)。后一种算法实际上是Goemans和Williamson [M.X. Goemans,D.P。 Williamson,一种用于约束森林问题的通用逼近技术,SIAM计算杂志24(2)(1995年4月)296-317]。我们的主要算法的另一种特殊情况是Bar-Yehuda的局部比率(广义Steiner森林问题的2-2 / n逼近(所有惩罚都是无穷大))[R. Bar-Yehuda,以两个价格为一:统一一种近似覆盖问题的方法,Algorithmica 27(2)(2000年6月)131-144]。因此,本文的重要贡献是对Goemans和Williamson,后来由Bar-Yehuda提出的框架进行了自然概括。

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