Improved methods for approximating node weighted Steiner trees and connected dominating sets

被引:123
作者
Guha, S [1 ]
Khuller, S
机构
[1] Stanford Univ, Dept Comp Sci, Stanford, CA 94305 USA
[2] Univ Maryland, Dept Comp Sci, College Pk, MD 20742 USA
[3] Univ Maryland, UMIACS, College Pk, MD 20742 USA
基金
美国国家科学基金会;
关键词
D O I
10.1006/inco.1998.2754
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
In this paper we study the Steiner tree problem in graphs for the case when vertices as well as edges have weights associated with them. A greedy approximation algorithm based on "spider decompositions" was developed by Klein and Ravi for this problem. This algorithm provides a worst case approximation ratio of 2 In k, where k is the number of terminals. However, the best known lower bound on the approximation ratio is (1 - o(1)) In k, assuming that NP not subset of or equal to DTIME[n(O(log log) (n))], by a reduction from set cover. We show that for the unweighted case we can obtain an approximation factor of In k. For the weighted case we develop a new decomposition theorem and generalize the notion of "spiders" to "branch-spiders" that are used to design a new algorithm with a worst case approximation factor of 1.5 In k. We then generalize the method to yield an approximation factor of (1.35 + epsilon) In k, for any constant epsilon > 0. These algorithms, although polynomial, are not very practical due to their high running time, since we need to repeatedly find many minimum weight matchings in each iteration. We also develop a simple greedy algorithm that is practical and has a worst case approximation factor of 1.6103 In k. The techniques developed for this algorithm imply a method of approximating node weighted network design problems defined by 0-1 proper functions as well. These new ideas also lead to improved approximation guarantees for the problem of finding a minimum node weighted connected dominating set. The previous best approximation guarantee for this problem was 3 In n by Guha and Khuller. By a direct application of the methods developed in this paper we are able to develop an algorithm with an approximation factor of (1.35 + epsilon) In n for any fixed epsilon > 0. (C) 1999 Academic Press.
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页码:57 / 74
页数:18
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