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Approximate k-MSTs and k-Steiner trees via the primal-dual method and Lagrangean relaxation
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Approximate k-MSTs and k-Steiner trees via the primal-dual method and Lagrangean relaxation Fabián A. Chudak1 , Tim Roughgarden2 and David P. Williamson3  | (1) | ETH Zurich, Institut für Operations Research, CLP D 7, Clausiusstrasse 45, 8092 Zürich, Switzerland |
| (2) | University of California at Berkeley, Computer Science Department, Soda Hall 587, Berkeley, CA 94720, USA |
| (3) | IBM Almaden Research Center, 650 Harry Rd, K53/B1, San Jose, CA, 95120, USA |
Received: 2 April 2002 Accepted: 15 September 2003 Published online: 9 January 2004 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.
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