2009 | OriginalPaper | Buchkapitel
A Heuristic Strong Connectivity Algorithm for Large Graphs
verfasst von : Adan Cosgaya-Lozano, Norbert Zeh
Erschienen in: Experimental Algorithms
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
We present a contraction-based algorithm for computing the strongly connected components of large graphs. While the worst-case complexity of the algorithm can be terrible (essentially the cost of running a DFS-based internal-memory algorithm on the entire graph), our experiments confirm that the algorithm performs remarkably well in practice. The strongest competitor is the algorithm by Sibeyn et al. [17], which is based on a semi-external DFS algorithm developed in the same paper. Our algorithm substantially outperforms the algorithm of [17] on most of the graphs used in our experiments and never performs worse. It thus demonstrates that graph contraction, which is the most important technique for solving connectivity problems on
undirected
graphs I/O-efficiently, can be used to solve such problems also on
directed
graphs, at least as a heuristic.