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Approximate k-MSTs and k-Steiner trees via the primal-dual method and Lagrangean relaxation
Authors:Fabián A.?Chudak,Tim?Roughgarden,David P.?Williamson  author-information"  >  author-information__contact u-icon-before"  >  mailto:dpw@almaden.ibm.com"   title="  dpw@almaden.ibm.com"   itemprop="  email"   data-track="  click"   data-track-action="  Email author"   data-track-label="  "  >Email author
Affiliation:(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
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 Gargrsquos 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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