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Shortest Path Tree Computation in Dynamic Graphs

机译:动态图中的最短路径树计算

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Let G = (V, E, w) be a simple digraph, in which all edge weights are nonnegative real numbers. Let G^{prime} be obtained from G by an application of a set of edge weight updates to G. Let sin V and let T_{s} and T_{s}^{prime} be Shortest Path Trees (SPTs) rooted at s in G and G^{prime}, respectively. The Dynamic Shortest Path (DSP) problem is to compute T_{s}^{prime} from T_{s}. Existing work on this problem focuses on either a single edge weight change or multiple edge weight changes in which some of them are incorrect or are not optimized. We correct and extend a few state-of-the-art dynamic SPT algorithms to handle multiple edge weight updates. We prove that these algorithms are correct. Dynamic algorithms may not outperform static algorithms all the time. To evaluate the proposed dynamic algorithms, we compare them with the well-known static Dijkstra algorithm. Extensive experiments are conducted with both real-life and artificial data sets. The experimental results suggest the most appropriate algorithms to be used under different circumstances.
机译:令G =(V,E,w)是一个简单的有向图,其中所有边缘权重均为非负实数。通过应用一组对G的边缘权重更新,从G获得G ^ {prime}。令sin V并使T_ {s}和T_ {s} ^ {prime}为根植于的最短路径树(SPT)。分别在G和G ^ {prime}中。动态最短路径(DSP)问题是从T_ {s}计算T_ {s} ^ {prime}。关于此问题的现有工作集中在单个边缘权重更改或多个边缘权重更改上,其中一些不正确或未优化。我们更正并扩展了一些最新的动态SPT算法,以处理多个边缘权重更新。我们证明这些算法是正确的。动态算法可能无法始终胜过静态算法。为了评估提出的动态算法,我们将它们与著名的静态Dijkstra算法进行比较。使用真实和人工数据集进行了广泛的实验。实验结果建议在不同情况下使用最合适的算法。

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