Approximate k-MSTs and k-Steiner trees via the primal-dual method and Lagrangean relaxation

Authors:
Fabián A. Chudak;Tim Roughgarden;David P. Williamson
Affiliations:
Institut für Operations Research, ETH Zurich, Switzerland;Computer Science Department, University of California at Berkeley, USA;IBM Almaden Research Center, University of California at Berkeley, USA
Venue:
Mathematical Programming: Series A and B
Year:
2004

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Abstract

Garg [10] gives two approximation algorithms for the minimum-cost tree spanning k vertices in an undirected graph. Recently Jain and Vazirani [15] discovered primal-dual approximation algorithms for the metric uncapacitated facility location and k-median problems. In this paper we show how Garg’s algorithms can be explained simply with ideas introduced by Jain and Vazirani, in particular via a Lagrangean relaxation technique together with the primal-dual method for approximation algorithms. We also derive a constant factor approximation algorithm for the k-Steiner tree problem using these ideas, and point out the common features of these problems that allow them to be solved with similar techniques.