A Branch and Bound Algorithm for Max-Cut Based on Combining Semidefinite and Polyhedral Relaxations

  • Franz Rendl
  • Giovanni Rinaldi
  • Angelika Wiegele
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4513)


In this paper we present a method for finding exact solutions of the Max-Cut problem max x T Lx such that x ∈ { − 1,1} n . We use a semidefinite relaxation combined with triangle inequalities, which we solve with the bundle method. This approach is due to [12] and uses Lagrangian duality to get upper bounds with reasonable computational effort. The expensive part of our bounding procedure is solving the basic semidefinite programming relaxation of the Max-Cut problem.

We review other solution approaches and compare the numerical results with our method. We also extend our experiments to unconstrained quadratic 0-1 problems and to instances of the graph bisection problem.

The experiments show, that our method nearly always outperforms all other approaches. Our algorithm, which is publicly accessible through the Internet, can solve virtually any instance with about 100 variables in a routine way.


Triangle Inequality Bundle Method Exact Ground State Johnson Graph Bisection Problem 
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 Berlin Heidelberg 2007

Authors and Affiliations

  • Franz Rendl
    • 1
  • Giovanni Rinaldi
    • 2
  • Angelika Wiegele
    • 1
  1. 1.Alpen-Adria-Universität Klagenfurt, Institut für Mathematik, Universitätsstr. 65-67, 9020 KlagenfurtAustria
  2. 2.Istituto di Analisi dei Sistemi ed Informatica “Antonio Ruberti” – CNR, Viale Manzoni, 30, 00185 RomaItaly

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