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A Memetic Approach for the Max-Cut Problem

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Parallel Problem Solving from Nature - PPSN XII (PPSN 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7492))

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Abstract

The max-cut problem is to partition the vertices of a weighted graph G = (V,E) into two subsets such that the weight sum of the edges crossing the two subsets is maximized. This paper presents a memetic max-cut algorithm (MACUT) that relies on a dedicated multi-parent crossover operator and a perturbation-based tabu search procedure. Experiments on 30 G-set benchmark instances show that MACUT competes favorably with 6 state-of-the-art max-cut algorithms, and for 10 instances improves on the best known results ever reported in the literature.

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Authors and Affiliations

  1. LERIA, Université d’Angers, 2 Boulevard Lavoisier, 49045, Angers Cedex 01, France

    Qinghua Wu & Jin-Kao Hao

Authors
  1. Qinghua Wu
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  2. Jin-Kao Hao
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Editor information

Editors and Affiliations

  1. Departmento de Computation, Centro de Investigacion y de Estudios, Avanzados del Instituto Politecnico Nacional (CINVESTAV-IPN), Av. IPN No. 2508, Col. San Pedro Zacatenco, 0360, Mexico, D.F., Mexico

    Carlos A. Coello Coello

  2. Department of Mathematics and Computer Science, University of Catania, V.le A. Doria 6, 95125, Catania, Italy

    Vincenzo Cutello  & Mario Pavone  & 

  3. Kanpur Genetic Algorithms Laboratory (KanGAL), Indian Institute of Technology, Kanpur, Kanpur, India

    Kalyanmoy Deb

  4. Department of Computer Science, University of New Mexico, USA

    Stephanie Forrest

  5. Department of Mathematics and Computer Science, University of Catania, Viale A. Doria 6, 95125, Catania, Italy

    Giuseppe Nicosia

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© 2012 Springer-Verlag Berlin Heidelberg

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Wu, Q., Hao, JK. (2012). A Memetic Approach for the Max-Cut Problem. In: Coello, C.A.C., Cutello, V., Deb, K., Forrest, S., Nicosia, G., Pavone, M. (eds) Parallel Problem Solving from Nature - PPSN XII. PPSN 2012. Lecture Notes in Computer Science, vol 7492. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32964-7_30

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  • DOI: https://doi.org/10.1007/978-3-642-32964-7_30

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32963-0

  • Online ISBN: 978-3-642-32964-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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