Approximating Minimum Multicuts by Evolutionary Multi-objective Algorithms

  • Frank Neumann
  • Joachim Reichel
Conference paper

DOI: 10.1007/978-3-540-87700-4_8

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5199)
Cite this paper as:
Neumann F., Reichel J. (2008) Approximating Minimum Multicuts by Evolutionary Multi-objective Algorithms. In: Rudolph G., Jansen T., Beume N., Lucas S., Poloni C. (eds) Parallel Problem Solving from Nature – PPSN X. PPSN 2008. Lecture Notes in Computer Science, vol 5199. Springer, Berlin, Heidelberg

Abstract

It has been shown that simple evolutionary algorithms are able to solve the minimum cut problem in expected polynomial time when using a multi-objective model of the problem. In this paper, we generalize these ideas to the NP-hard minimum multicut problem. Given a set of k terminal pairs, we prove that evolutionary algorithms in combination with a multi-objective model of the problem are able to obtain a k-approximation for this problem in expected polynomial time.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Frank Neumann
    • 1
  • Joachim Reichel
    • 2
  1. 1.Max-Planck-Institut für InformatikSaarbrückenGermany
  2. 2.Institut für MathematikTU BerlinGermany

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