Asymmetry in k-center variants

Citations of this article
Mendeley users who have this article in their library.
Get full text


This paper explores three concepts: the k-center problem, some of its variants, and asymmetry. The k-center problem is a fundamental clustering problem, similar to the k-median problem. Variants of k-center may more accurately model real-life problems than the original formulation. Asymmetry is a significant impediment to approximation in many graph problems, such as k-center, facility location, k-median and the TSP. We demonstrate an O(log* n)-approximation algorithm for the asymmetric weighted k-center problem. Here, the vertices have weights and we are given a total budget for opening centers. In the p-neighbor variant each vertex must have p (unweighted) centers nearby: we give an O(log* k)-bicriteria algorithm using 2k centers, for small p. Finally, the following three versions of the asymmetric k-center problem we show to be inapproximable: priority k-center, k-supplier, and outliers with forbidden centers. © Springer-Verlag Berlin Heidelberg 2003.




Gørtz, I. L., & Wirth, A. (2003). Asymmetry in k-center variants. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2764, 59–70.

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free