论文标题

关于强大设施位置问题的静态分配政策的力量

On the Power of Static Assignment Policies for Robust Facility Location Problems

论文作者

Housni, Omar El, Goyal, Vineet, Shmoys, David

论文摘要

在不确定的需求下,我们考虑了在度量方面的两个阶段强大的设施位置问题。决策者需要在第一阶段确定每个设施的(整体)供应单位,以满足不确定的第二阶段需求,以便将第一阶段供应成本的总和和满足所有情况下满足所有情况的最糟糕的成本。第二阶段的决定仅是任务决定,而无需增加追索权供应能力。这使我们的模型与在两阶段可靠的设施位置的现有工作不同,并设置了覆盖问题。我们考虑了一个隐式不确定性模型,其中第二阶段客户端的上限$ k $指定的需求方案数量。在最佳解决方案中,第二阶段的分配决策取决于场景。出乎意料的是,我们证明了每个潜在客户端的固定(静态)分配分配的限制,而不管方案如何,我们的问题就会给我们一个$ O(\ log k/\ log \ log \ log k)$ - 近似问题的近似值。此外,可以有效地计算出最好的静态分配,从而为我们提供所需的保证。

We consider a two-stage robust facility location problem on a metric under an uncertain demand. The decision-maker needs to decide on the (integral) units of supply for each facility in the first stage to satisfy an uncertain second-stage demand, such that the sum of first stage supply cost and the worst-case cost of satisfying the second-stage demand over all scenarios is minimized. The second-stage decisions are only assignment decisions without the possibility of adding recourse supply capacity. This makes our model different from existing work on two-stage robust facility location and set covering problems. We consider an implicit model of uncertainty with an exponential number of demand scenarios specified by an upper bound $k$ on the number of second-stage clients. In an optimal solution, the second-stage assignment decisions depend on the scenario; surprisingly, we show that restricting to a fixed (static) fractional assignment for each potential client irrespective of the scenario gives us an $O(\log k/\log \log k)$-approximation for the problem. Moreover, the best such static assignment can be computed efficiently giving us the desired guarantee.

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