This paper aims to improve the average response time for naval accidents in the North and Baltic Sea. To do this we optimize the strategic distribution of the vessel fleet used by the Deutsche Gesellschaft zur Rettung Schiffbr\"uchiger (German Maritime Search and Rescue Service) (DGzRS) across several home stations. Based on these locations, in case of an incoming distress call the vessel with the lowest response time is dispatched. A particularity of the region considered is the fact that due to low tide, at predictable times some vessels and stations are not operational. In our work, we build a corresponding mathematical model for the allocation of rescue crafts to multiple stations. Thereafter, we show that the problem is NP-hard. Next, we provide an Integer Programming (IP) formulation. Finally, we propose several methods of simplifying the model and do a case study to compare their effectiveness. For this, we generate test instances based on real-world data.

翻译：本文旨在提高北海与波罗的海海上事故的平均响应时间。为此，我们优化了德国海上搜救服务协会（DGzRS）所用船队在其多个母站之间的战略分布。基于这些位置，在接到求救呼叫时，会选择响应时间最短的船只进行派遣。该区域的一个特殊性是，由于低潮，在可预测的时间段内，某些船只和站点无法运行。在我们的工作中，我们构建了一个相应的数学模型来分配救援船到多个站点。随后，我们证明了该问题是NP难的。接着，我们提供了一个整数规划（IP）公式。最后，我们提出了几种简化模型的方法，并通过案例研究来比较它们的有效性。为此，我们基于真实数据生成了测试实例。