The reverse greedy algorithm for the metric k-median problem
Data Structures and Algorithms
2015-06-02 v2
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 ?(log n/ log log n) and O(log n).
Cite
@article{arxiv.cs/0504104,
title = {The reverse greedy algorithm for the metric k-median problem},
author = {Marek Chrobak and Claire Kenyon and Neal E. Young},
journal= {arXiv preprint arXiv:cs/0504104},
year = {2015}
}
Comments
to appear in IPL. preliminary version in COCOON '05