English

Capacitated Center Problems with Two-Sided Bounds and Outliers

Data Structures and Algorithms 2017-02-27 v1

Abstract

In recent years, the capacitated center problems have attracted a lot of research interest. Given a set of vertices VV, we want to find a subset of vertices SS, called centers, such that the maximum cluster radius is minimized. Moreover, each center in SS should satisfy some capacity constraint, which could be an upper or lower bound on the number of vertices it can serve. Capacitated kk-center problems with one-sided bounds (upper or lower) have been well studied in previous work, and a constant factor approximation was obtained. We are the first to study the capacitated center problem with both capacity lower and upper bounds (with or without outliers). We assume each vertex has a uniform lower bound and a non-uniform upper bound. For the case of opening exactly kk centers, we note that a generalization of a recent LP approach can achieve constant factor approximation algorithms for our problems. Our main contribution is a simple combinatorial algorithm for the case where there is no cardinality constraint on the number of open centers. Our combinatorial algorithm is simpler and achieves better constant approximation factor compared to the LP approach.

Keywords

Cite

@article{arxiv.1702.07435,
  title  = {Capacitated Center Problems with Two-Sided Bounds and Outliers},
  author = {Hu Ding and Lunjia Hu and Lingxiao Huang and Jian Li},
  journal= {arXiv preprint arXiv:1702.07435},
  year   = {2017}
}
R2 v1 2026-06-22T18:27:02.644Z