Algorithm Engineering for Optimal Graph Bipartization

  • Falk Hüffner
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3503)


We examine exact algorithms for the NP-complete Graph Bipartization problem that asks for a minimum set of vertices to delete from a graph to make it bipartite. Based on the “iterative compression” method recently introduced by Reed, Smith, and Vetta, we present new algorithms and experimental results. The worst-case time complexity is improved from O(3 k · kmn) to O(3 k · mn), where n is the number of vertices, m is the number of edges, and k is the number of vertices to delete. Our best algorithm can solve all problems from a testbed from computational biology within minutes, whereas established methods are only able to solve about half of the problems within reasonable time.


Random Graph Integer Linear Program Dense Graph Auxiliary Graph Optimal Graph 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Falk Hüffner
    • 1
  1. 1.Institut für InformatikFriedrich-Schiller-Universität JenaJena

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