The reverse greedy algorithm for the metric K-median problem

Authors:
Marek Chrobak;Claire Kenyon;Neal E. Young
Affiliations:
Department of Computer Science, University of California, Riverside, CA;Computer Science Department, Brown University, Providence, RI;Department of Computer Science, University of California, Riverside, CA
Venue:
COCOON'05 Proceedings of the 11th annual international conference on Computing and Combinatorics
Year:
2005

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Abstract

The Reverse Greedy algorithm (RGreedy) for the k-median problem works as follows. It starts by placing facilities on all nodes. At each step, it removes a facility to minimize the resulting total distance from the customers to the remaining facilities. It stops when k facilities remain. We prove that, if the distance function is metric, then the approximation ratio of RGreedy is between Ω(log n/loglog n) and O(log n).