Word RAM上的Delaunay三角剖分:一种实用的最坏情况最优算法

Okke Schrijvers, F.F.J.M. van Bommel, K. Buchin
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引用次数: 5

摘要

平面上n个点的Delaunay三角剖分可以在o(n log n)时间内构造,当点的坐标是有限范围内的整数时。然而,到目前为止,还没有实现实现这样的运行时间的算法。我们探索了在线性时间平面上求解小整数的Delaunay三角剖分的实用算法。为此,我们首先实现并评估BrioDC的两个变体,BrioDC是一种已知可以实现此界限的算法。我们实现了第一个O(n)时间算法来构造Delaunay三角,并发现我们的实现是实用的。虽然对于现实数据集,我们没有改进现有的快速算法(非最优最坏情况运行时间),但我们的BrioDC实现确实让我们了解了点定位所需的最佳时间。其次,我们实现并评估BRIO的变体,BRIO算法在小整数上的最坏情况运行时间为O(n log n),但在许多分布下运行速度更快。我们的变体旨在避免最坏的情况,这是由于高点位置时间。我们的BrioDC实现表明,点定位时间可以减少25%,我们的平方空间填充曲线顺序显示了第一个改进,减少了3%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Delaunay Triangulations on the Word RAM: Towards a Practical Worst-Case Optimal Algorithm
The Delaunay triangulation of n points in the plane can be constructed in o(n log n) time when the coordinates of the points are integers from a restricted range. However, algorithms that are known to achieve such running times had not been implemented so far. We explore ways to obtain a practical algorithm for Delaunay triangulations in the plane that runs in linear time for small integers. For this, we first implement and evaluate two variants of BrioDC, an algorithm that is known to achieve this bound. We implement the first O(n)-time algorithm for constructing Delaunay triangulations and found that our implementations are practical. While we do not improve upon fast existing algorithms (with non-optimal worst-case running time) for realistic data sets, our BrioDC implementations do give us insight into the optimal time needed for point location. Secondly, we implement and evaluate variants of BRIO, an algorithm which has an O(n log n) worst-case running time on small integers but runs faster for many distributions. Our variants aim to avoid bad worst-case behavior, which is due to high point location time. Our BrioDC implementation shows that point location time can be reduced by 25% and our squarified space-filling curve orders show the first improvement by reducing this by 3%.
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