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An effective heuristic for computing many shortest path alternatives in road networks

机译:一种有效的启发式算法,可计算道路网络中的许多最短路径

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摘要

We propose a simple and effective heuristic that allows fast generation of a large set of shortest path alternatives in weighted directed graphs. The heuristic is based on existing deviation path algorithms for exact k shortest paths. It precalculates a backward shortest path tree and thus avoids doing many shortest path computations, but as a result it does not necessarily find the exact set of k shortest paths. Computational results on real-world road networks are reported. Our tests show that the quality of the paths produced by the heuristic is most satisfactory: typically, the kth path found by the heuristic is less than 1 % longer than the exact kth shortest path, for values of k up to 10,000. Moreover, the heuristic runs very fast. We also show how the heuristic can be enhanced to an exact k shortest paths algorithm, which performs well in comparison with the existing exact k shortest path algorithms.
机译:我们提出了一种简单有效的启发式方法,可以在加权有向图中快速生成大量最短路径替代方案。启发式算法基于现有的偏差路径算法,用于精确的k条最短路径。它预先计算了向后的最短路径树,因此避免了进行许多最短路径计算,但结果是不一定找到精确的k条最短路径集。报告了现实世界道路网络上的计算结果。我们的测试表明,启发式方法产生的路径质量最令人满意:通常,对于k值高达10,000的情况,启发式方法找到的第k条路径比确切的第k条最短路径长不到1%。此外,启发式算法运行非常快。我们还展示了如何将启发式算法增强为精确的k最短路径算法,与现有的精确k最短路径算法相比,该算法表现良好。

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