有界度平面几何扳手的实践

Q2 Mathematics
Fred Anderson, Anirban Ghosh, Matthew Graham, Lucas Mougeot, David Wisnosky
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引用次数: 1

摘要

自2002年Bose、Gudmundsson和Smid提出构造有界度平面几何扳手的第一个算法以来,有界度平面几何扳手的构造一直是关注的焦点。迄今为止,已经设计了11种算法,在程度和拉伸因子方面进行了各种权衡。我们使用CGAL库在c++中实现了这些复杂的扳手算法,并使用大型合成点集和现实世界的点集对它们进行了实验。我们的实验揭示了它们的实际行为和现实世界的功效。我们通过GitHub分享实现,以供更广泛的使用和未来的研究。我们设计和工程estimatestrechfactor,一个简单实用的算法,可以估计几何扳手的拉伸因子(获得确切拉伸因子的下界)-这是一个具有挑战性的问题,目前还没有实用的算法。在我们的有界度平面几何扳手实验中,我们发现estimatestrechfactor几乎精确地估计拉伸因子。此外,它在实践中为本工作中考虑的点集分布提供了线性运行时性能,使其在计算拉伸因子时比基于朴素dijkstra的算法快得多。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bounded-degree Plane Geometric Spanners in Practice
The construction of bounded-degree plane geometric spanners has been a focus of interest since 2002 when Bose, Gudmundsson, and Smid proposed the first algorithm to construct such spanners. To date, eleven algorithms have been designed with various trade-offs in degree and stretch-factor. We have implemented these sophisticated spanner algorithms in C++ using the CGAL library and experimented with them using large synthetic and real-world pointsets. Our experiments have revealed their practical behavior and real-world efficacy. We share the implementations via GitHub for broader uses and future research. We design and engineer EstimateStretchFactor, a simple practical algorithm, that can estimate stretch-factors (obtains lower bounds on the exact stretch-factors) of geometric spanners – a challenging problem for which no practical algorithm is known yet. In our experiments with bounded-degree plane geometric spanners, we found that EstimateStretchFactor estimated stretch-factors almost precisely. Further, it gave linear runtime performance in practice for the pointset distributions considered in this work, making it much faster than the naive Dijkstra-based algorithm for calculating stretch-factors.
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来源期刊
Journal of Experimental Algorithmics
Journal of Experimental Algorithmics Mathematics-Theoretical Computer Science
CiteScore
3.10
自引率
0.00%
发文量
29
期刊介绍: The ACM JEA is a high-quality, refereed, archival journal devoted to the study of discrete algorithms and data structures through a combination of experimentation and classical analysis and design techniques. It focuses on the following areas in algorithms and data structures: ■combinatorial optimization ■computational biology ■computational geometry ■graph manipulation ■graphics ■heuristics ■network design ■parallel processing ■routing and scheduling ■searching and sorting ■VLSI design
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