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首页> 外文期刊>LIPIcs : Leibniz International Proceedings in Informatics >Constant Factor Approximation Algorithm for Uniform Hard Capacitated Knapsack Median Problem
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Constant Factor Approximation Algorithm for Uniform Hard Capacitated Knapsack Median Problem

机译:均匀硬容量背包中值问题的常因子近似算法。

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摘要

In this paper, we give the first constant factor approximation algorithm for capacitated knapsack median problem (CKnM) for hard uniform capacities, violating the budget by a factor of 1+epsilon and capacities by a 2+epsilon factor. To the best of our knowledge, no constant factor approximation is known for the problem even with capacity/budget/both violations. Even for the uncapacitated variant of the problem, the natural LP is known to have an unbounded integrality gap even after adding the covering inequalities to strengthen the LP. Our techniques for CKnM provide two types of results for the capacitated k-facility location problem. We present an O(1/epsilon^2) factor approximation for the problem, violating capacities by (2+epsilon). Another result is an O(1/epsilon) factor approximation, violating the capacities by a factor of at most (1 + epsilon) using at most 2k facilities for a fixed epsilon0. As a by-product, a constant factor approximation algorithm for capacitated facility location problem with uniform capacities is presented, violating the capacities by (1 + epsilon) factor. Though constant factor results are known for the problem without violating the capacities, the result is interesting as it is obtained by rounding the solution to the natural LP, which is known to have an unbounded integrality gap without violating the capacities. Thus, we achieve the best possible from the natural LP for the problem. The result shows that the natural LP is not too bad.
机译:在本文中,我们给出了针对硬均等容量的带帽背包中位数问题(CKnM)的第一个常数因子近似算法,这使预算违反了1 +ε的要求,而违反了2 +ε的要求。据我们所知,即使存在容量/预算/两者均违反的情况,也没有已知的恒定因子近似值可解决该问题。即使对于问题的无能力解,即使添加了覆盖不等式以增强LP,自然LP仍具有无限的完整性缺口。我们针对CKnM的技术针对容量受限的k设施位置问题提供了两种类型的结果。我们提出了该问题的O(1 /ε^ 2)因子近似值,违反了(2 +ε)的容量。另一个结果是O(1 / epsilon)因子近似值,对于固定epsilon> 0,使用最多2k的设施最多将容量乘以最大(1 + epsilon)倍。作为副产品,提出了一种具有均等容量的容量受限设施选址问题的常数因子近似算法,该算法违反了容量(1 +ε)因子。尽管在不破坏容量的情况下就可以得到恒定因子的结果,但结果却很有趣,因为它是通过对自然LP进行四舍五入而获得的,自然LP在不破坏容量的情况下具有无穷大的积分缺口。这样,我们就可以从自然LP中获得最大的收益。结果表明自然LP不太差。

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