The reverse greedy algorithm for the metric k-median problem

Authors:
Marek Chrobak;Claire Kenyon;Neal Young
Affiliations:
Department of Computer Science, University of California, Riverside, CA 92521, USA;Computer Science Department, Brown University, Providence, RI 02912, USA;Department of Computer Science, University of California, Riverside, CA 92521, USA
Venue:
Information Processing Letters
Year:
2006

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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 total distance 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 @W(logn/loglogn) and O(logn).