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Quasi-polynomial Time Approximation Algorithm for Low-Degree Minimum-Cost Steiner Trees

机译:低度最小成本施坦拌续树的准多项式时间近似算法

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In a recent paper [5], we addressed the problem of finding a minimum-cost spanning tree T for a given undirected graph G = (V,E) with maximum node-degree at most a given parameter B > 1. We developed an algorithm based on Lagrangean relaxation that uses a repeated application of Kruskal's MST algorithm interleaved with a combinatorial update of approximate Lagrangean node-multipliers maintained by the algorithm. In this paper, we show how to extend this algorithm to the case of Steiner trees where we use a primal-dual approximation algorithm due to Agrawal, Klein, and Ravi [1] in place of Kruskal's minimum-cost spanning tree algorithm. The algorithm computes a Steiner tree of maximum degree O(B + logn) and total cost that is within a constant factor of that of a minimum-cost Steiner tree whose maximum degree is bounded by B. However, the running time is quasi-polynomial.
机译:在最近的一篇论文中,我们解决了在大多数给定参数B> 1的最大节点度的给定无向图G =(v,e)的最小节点度的最小成本跨越树t的问题。我们开发了一个基于Lagrangean松弛的算法,其使用算法维持的近似拉格朗族节点乘法器的组合更新的Kruskal的MST算法交织的重复应用。在本文中,我们展示了如何将该算法扩展到Steiner树的情况,其中我们使用由于Agrawal,Klein和Ravi [1]代替kruskal最小成本生成树算法的原始 - 双近似算法。该算法计算最大程度o(b + logn)的施蒂纳树,以及在最大程度界定的最小度施蒂纳树的恒定因子的总成本,其最大程度为b。但是,运行时间是准多项式。

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