A Partition-Based Relaxation For Steiner Trees
Jochen Konemann, David Pritchard, Kunlun Tan

TL;DR
This paper introduces a new partition-based linear programming relaxation for the Steiner tree problem, linking greedy and LP approaches, and provides improved approximation guarantees for specific graph classes.
Contribution
It establishes a primal-dual interpretation of Robins and Zelikovsky's algorithm via a novel LP relaxation and demonstrates its strength over existing formulations.
Findings
The new LP is stronger than the bidirected cut formulation.
Robins and Zelikovsky's algorithm has better ratios on b-quasi-bipartite instances.
The integrality gap of the LP is bounded between 8/7 and (2b+1)/(b+1).
Abstract
The Steiner tree problem is a classical NP-hard optimization problem with a wide range of practical applications. In an instance of this problem, we are given an undirected graph G=(V,E), a set of terminals R, and non-negative costs c_e for all edges e in E. Any tree that contains all terminals is called a Steiner tree; the goal is to find a minimum-cost Steiner tree. The nodes V R are called Steiner nodes. The best approximation algorithm known for the Steiner tree problem is due to Robins and Zelikovsky (SIAM J. Discrete Math, 2005); their greedy algorithm achieves a performance guarantee of 1+(ln 3)/2 ~ 1.55. The best known linear (LP)-based algorithm, on the other hand, is due to Goemans and Bertsimas (Math. Programming, 1993) and achieves an approximation ratio of 2-2/|R|. In this paper we establish a link between greedy and LP-based approaches by showing that Robins and…
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Taxonomy
TopicsComplexity and Algorithms in Graphs · VLSI and FPGA Design Techniques · Advanced Graph Theory Research
