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

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FSTTCS 2007: Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4855))

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 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.

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V. Arvind Sanjiva Prasad

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Jakoby, A., Tantau, T. (2007). Logspace Algorithms for Computing Shortest and Longest Paths in Series-Parallel Graphs. In: Arvind, V., Prasad, S. (eds) FSTTCS 2007: Foundations of Software Technology and Theoretical Computer Science. FSTTCS 2007. Lecture Notes in Computer Science, vol 4855. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77050-3_18

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  • DOI: https://doi.org/10.1007/978-3-540-77050-3_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-77049-7

  • Online ISBN: 978-3-540-77050-3

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