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Approximate Shortest Path Queries Using Voronoi Duals

机译:使用Voronoi对偶的近似最短路径查询

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We propose an approximation method to answer point-to-point shortest path queries in undirected edge-weighted graphs, based on random sampling and Voronoi duals. We compute a simplification of the graph by selecting nodes independently at random with probability p. Edges are generated as the Voronoi dual of the original graph, using the selected nodes as Voronoi sites. This overlay graph allows for fast computation of approximate shortest paths for general, undirected graphs. The time-quality tradeoff decision can be made at query time. We provide bounds on the approximation ratio of the path lengths as well as experimental results. The theoretical worst-case approximation ratio is bounded by a logarithmic factor. Experiments show that our approximation method based on Voronoi duals has extremely fast preprocessing time and efficiently computes reasonably short paths.
机译:基于随机采样和Voronoi对偶,我们提出一种近似方法来回答无向边加权图中点对点最短路径查询。我们通过以概率p随机随机选择节点来计算图的简化。使用选定的节点作为Voronoi站点,将边生成为原始图形的Voronoi对偶。此覆盖图允许快速计算通用无向图的近似最短路径。时间质量折衷决定可以在查询时做出。我们提供了路径长度的近似比率以及实验结果的界限。理论上的最坏情况下的近似比率受对数因子限制。实验表明,我们基于Voronoi对偶的逼近方法具有非常快的预处理时间,并且可以有效地计算合理的短路径。

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