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Local Search Algorithms for the Red-Blue Median Problem

机译:红蓝中值问题的局部搜索算法

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摘要

In this paper, we consider the following red-blue median problem which is a generalization of the well-studied k-median problem. The input consists of a set of red facilities, a set of blue facilities, and a set of clients in a metric space and two integers k_r, k_b > 0. The problem is to open at most k_r red facilities and at most k_b blue facilities and minimize the sum of distances of clients to their respective closest open facilities. We show, somewhat surprisingly, that the following simple local search algorithm yields a constant factor approximation for this problem. Start by opening any k_r red and k_b blue facilities. While possible, decrease the cost of the solution by closing a pair of red and blue facilities and opening a pair of red and blue facilities. We also improve the approximation factor for the prize-collecting k-median problem from 4 (Charikar et al. in Proceedings of the ACM-SIAM Symposium on Discrete Algorithms, pp. 642-641, 2001) to 3 + ∈, which matches the current best approximation factor for the k-median problem.
机译:在本文中,我们考虑以下红色-蓝色中值问题,它是经过充分研究的k中值问题的推广。输入由一组红色设施,一组蓝色设施以及一组度量空间中的客户端和两个整数k_r,k_b> 0组成。问题是要打开最多k_r个红色设施和最多k_b个蓝色设施并最大程度地减少客户到各自最近的开放设施的距离之和。我们出乎意料地表明,以下简单的本地搜索算法可得出此问题的常数因子近似值。首先打开任何k_r红色和k_b蓝色功能。如果可能,请关闭一对红色和蓝色设施并打开一对红色和蓝色设施,以降低解决方案的成本。我们还将奖品收集k中位数问题的近似因子从4(Charikar等人,在ACM-SIAM离散算法研讨会论文集,第642-641页,2001年)中提高到3 +∈,与k中值问题的当前最佳近似因子。

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