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Tight Approximation Bounds for Greedy Frugal Coverage Algorithms

机译:贪婪的节俭覆盖算法的紧逼近界

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We consider the frugal coverage problem, an interesting variation of set cover defined as follows. Instances of the problem consist of a universe of elements and a collection of sets over these elements; the objective is to compute a subcollection of sets so that the number of elements it covers plus the number of sets not chosen is maximized. The problem was introduced and studied by Huang and Svitkina [7] due to its connections to the donation center location problem. We prove that the greedy algorithm has approximation ratio at least 0.782, improving a previous bound of 0.731 in [7]. We also present a further improvement that is obtained by adding a simple corrective phase at the end of the execution of the greedy algorithm. The approximation ratio achieved in this way is at least 0.806. Our analysis is based on the use of linear programs which capture the behavior of the algorithms in worst-case examples. The obtained bounds are proved to be tight.
机译:我们考虑节俭覆盖率问题,这是布景覆盖率的一个有趣变化,定义如下。问题的实例包括一系列元素以及这些元素上的集合的集合;目的是计算集合的子集合,以使其覆盖的元素数量加上未选择的集合数量最大化。这个问题是由Huang和Svitkina [7]引入和研究的,因为它与捐赠中心的位置问题有关。我们证明贪婪算法的逼近率至少为0.782,从而提高了[7]中的0.731的先前范围。我们还提出了进一步的改进,该改进是通过在贪婪算法执行结束时添加一个简单的校正阶段来实现的。以这种方式获得的近似比至少为0.806。我们的分析基于线性程序的使用,该程序在最坏的情况下捕获了算法的行为。证明所获得的边界是紧密的。

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