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 $\alpha$ 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 $\ell$.
翻译:我们研究以美元为中位数的集成集成法,首先由Kavand等人介绍,我们没有建立一套中心,而是有两种类型的中心,即红色和蓝色,每个红色中心至少距离每个蓝色中心1美元。目标是将覆盖半径最小化。我们为这一问题提供一个近似算法,并为受限问题提供一个多元时间算法,所有中心都必须处于1行1美元。