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Logspace Algorithms for Computing Shortest and Longest Paths in Series-Parallel Graphs

机译:用于计算串联图形中最短和最长路径的LogSpace算法

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For many types of graphs, including directed acyclic graphs, undirected graphs, tournament graphs, and graphs with bounded independence number, the shortest path problem is NL-complete. The longest path problem is even NP-complete for many types of graphs, including undirected K 5-minor-free graphs and planar graphs. In the present paper we present logspace algorithms for computing shortest and longest paths in series-parallel graphs where the edges can be directed arbitrarily. The class of series-parallel graphs that we study can be characterized alternatively as the class of K 4-minor-free graphs and also as the class of graphs of tree-width 2. It is well-known that for graphs of bounded tree-width many intractable problems can be solved efficiently, but previous work was focused on finding algorithms with low parallel or sequential time complexity. In contrast, our results concern the space complexity of shortest and longest path problems. In particular, our results imply that for directed graphs of tree-width 2 these problems are L-complete.
机译:对于许多类型的图表,包括指示的非循环图,无向图形,锦标集图和具有有界独立号的图形,最短路径问题是NL-Complete。对于许多类型的图表,最长的路径问题甚至是NP - 完整的,包括无向k 5微量图形和平面图。在本文中,我们将Logspace算法呈现用于计算串联平行图中的最短和最长路径,其中边缘可以任意定向。我们学习的串行平行图表可以作为k 4 - 次次自由图类的类别,也可以作为树宽2的图形。众所周知,对于有界树的图形 - 宽度可以有效地解决了许多难治性问题,但之前的工作集中在寻找具有低平行或连续时间复杂度的算法。相比之下,我们的结果涉及最短和最长路径问题的空间复杂性。特别是,我们的结果意味着,对于树宽2的指向图,这些问题是L-Treating。

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