Logspace algorithms for computing shortest and longest paths in series-parallel graphs

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Abstract

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 K5-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 treewidth 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. © Springer-Verlag Berlin Heidelberg 2007.

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APA

Jakoby, A., & Tantau, T. (2007). Logspace algorithms for computing shortest and longest paths in series-parallel graphs. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4855 LNCS, pp. 216–227). Springer Verlag. https://doi.org/10.1007/978-3-540-77050-3_18

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