This paper addresses a graph optimization problem, called the Witness Tree problem, which seeks a spanning tree of a graph minimizing a certain non-linear objective function. This problem is of interest because it plays a crucial role in the analysis of the best approximation algorithms for two fundamental network design problems: Steiner Tree and Node-Tree Augmentation. We will show how a wiser choice of witness trees leads to an improved approximation for Node-Tree Augmentation, and for Steiner Tree in special classes of graphs.
翻译:本文涉及一个图形优化问题,称为证人树问题,它寻求一棵图的横树,最大限度地减少某种非线性目标功能。这个问题值得关注,因为它在分析两个基本网络设计问题的最佳近似算法方面发挥着关键作用:施泰纳树和诺德-特里增殖。我们将展示如何更明智地选择证人树,从而改进节点-特里增殖的近似值,以及特殊图表类中的施泰纳树。