Separated Red Blue Center Clustering

Abstract

We study a generalization of k-center clustering, first introduced by Kavand et. al., where instead of one set of centers, we have two types of centers, p red and q blue, and where each red center is at least α distant from each blue center. The goal is to minimize the covering radius. We provide an approximation algorithm for this problem, and a polynomial-time algorithm for the constrained problem, where all the centers must lie on a line ℓ.

Publication Title

Leibniz International Proceedings in Informatics, LIPIcs

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