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Algorithm 966: A Practical Iterative Algorithm for the Art Gallery Problem Using Integer Linear Programming

机译:算法966:使用整数线性规划的画廊问题实用迭代算法

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In the last few decades, the search for exact algorithms for known NP-hard geometric problems has intensified. Many of these solutions use Integer Linear Programming (ILP) modeling and rely on state-of-the- art solvers to be able to find optimal solutions for large instances in a matter of minutes. In this work, we discuss an ILP-based algorithm that solves to optimality the Art Gallery Problem (AGP), one of the most studied problems in computational geometry. The basic idea of our method is to iteratively generate upper and lower bounds for the problem through the resolution of discretized versions of the AGP, which are reduced to instances of the Set Cover Problem. Our algorithm was implemented and tested on almost 3,000 instances and attained optimal solutions for the vast majority of them, greatly increasing the set of instances for which exact solutions are known. To the best of our knowledge, in spite of the extensive study of the AGP in the last four decades, no other algorithm has shown the ability to solve the AGP as effectively and efficiently as the one described here. Evidence of its robustness is presented through tests done on a number of classes of polygons of various sizes with and without holes. A software package implementing the algorithm is made available.
机译:在过去的几十年中,对于已知的NP困难的几何问题的精确算法的搜索日益增多。这些解决方案中的许多解决方案都使用整数线性规划(ILP)建模,并依赖最新的求解器,从而能够在几分钟内为大型实例找到最佳解决方案。在这项工作中,我们讨论了一种基于ILP的算法,该算法可以最佳解决美术馆问题(AGP),这是计算几何学中研究最多的问题之一。我们方法的基本思想是通过解决AGP离散版本的问题来迭代生成问题的上限和下限,将其简化为“设置覆盖问题”的实例。我们的算法已在近3,000个实例上实施和测试,并为绝大多数实例获得了最佳解决方案,从而大大增加了已知确切解决方案的实例集。据我们所知,尽管在过去的40年中对AGP进行了广泛的研究,但没有其他算法能够像在此描述的那样有效和高效地解决AGP的问题。通过对各种大小的带孔和不带孔的多边形进行测试,可以证明其鲁棒性。提供了实现该算法的软件包。

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