Quasi-polynomial time approximation algorithm for low-degree minimum-cost steiner trees

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Abstract

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 + log n) 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. © Springer-Verlag Berlin Heidelberg 2003.

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Könemann, J., & Ravi, R. (2003). Quasi-polynomial time approximation algorithm for low-degree minimum-cost steiner trees. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2914, 289–301. https://doi.org/10.1007/978-3-540-24597-1_25

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