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Solving Geometric Covering Problems by Data Reduction

机译:通过数据减少解决几何覆盖问题

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We consider a scenario where stops are to be placed along an already existing public transportation network in order to improve its attractiveness for the customers. The core problem is a geometric set covering problem which is AfV-iiead in general. However, if the corresponding covering matrix has the consecutive ones property, it is solvable in polynomial time. In this paper, we present data reduction techniques for set covering and report on an experimental study considering real world data from railway systems as well as generated instances. The results show that data reduction works very well on instances that are in some sense "close" to having the consecutive ones property. In fact, the real world instances considered could be reduced significantly, in most cases even to triviality. The study also confirms and explains findings on similar techniques for related problems.
机译:我们考虑沿着现有的公共交通网络沿着现有的公共交通网络放置停止的情况,以提高客户对客户的吸引力。核心问题是几何设置覆盖问题,其通常是AFV-IIED。但是,如果相应的覆盖矩阵具有连续的属性,则它在多项式时间中可溶解。在本文中,我们展示了在考虑来自铁路系统的真实世界数据以及生成的实例的实验研究中的数据缩减技术。结果表明,数据减少在某种意义上“关闭”到具有连续属性的情况下运行。事实上,在大多数情况下,考虑的真实世界实例可以显着减少,即使是琐事。该研究还证实并解释了关于相关问题的类似技能的结果。

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