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A Backbone-Based Co-evolutionary Heuristic for Partial MAX-SAT

  • Conference paper
Artificial Evolution (EA 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3871))

Abstract

The concept of backbone variables in the satisfiability problem has been recently introduced as a problem structure property and shown to influence its complexity. This suggests that the performance of stochastic local search algorithms for satisfiability problems can be improved by using backbone information. The Partial MAX-SAT Problem (PMSAT) is a variant of MAX-SAT which consists of two CNF formulas defined over the same variable set. Its solution must satisfy all clauses of the first formula and as many clauses in the second formula as possible. This study is concerned with the PMSAT solution in setting a co-evolutionary stochastic local search algorithm guided by an estimated backbone variables of the problem. The effectiveness of our algorithm is examined by computational experiments. Reported results for a number of PMSAT instances suggest that this approach can outperform state-of-the-art PMSAT techniques.

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Author information

Authors and Affiliations

  1. Laboratoire d’Intelligence Artificielle, Université de Paris8, 2 rue de la liberté, 93526, Saint-Denis, France

    Mohamed El Bachir Menaï

  2. Laboratoire LIRE, Département d’Informatique, Université Mentouri, 25000, Constantine, Algérie

    Mohamed Batouche

Authors
  1. Mohamed El Bachir Menaï
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  2. Mohamed Batouche
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Editor information

Editors and Affiliations

  1. INRIA Lille - Nord Europe Research Centre, Parc Scientifique de la Haute Borne, 59650, Villeneuve d’Ascq, France

    El-Ghazali Talbi

  2. UMR-CNRS 6632, Université de Provence, 39 rue F. Joliot-Curie, 13453, Marseille cedex 13, France

    Pierre Liardet

  3. Université Louis Pasteur, LSIIT, FDBT, Pôle API, F-67400, Illkirch, France

    Pierre Collet

  4. INRIA Saclay - Ile-de-France, Parc Orsay Université, 4, rue Jacques Monod, 91893, ORSAY Cedex, France

    Evelyne Lutton

  5. TAO, INRIA Saclay & LRI (UMR CNRS 8623), Bât 490, Université Paris-Sud, 91405, Orsay Cedex, France

    Marc Schoenauer

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© 2006 Springer-Verlag Berlin Heidelberg

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Menaï, M.E.B., Batouche, M. (2006). A Backbone-Based Co-evolutionary Heuristic for Partial MAX-SAT. In: Talbi, EG., Liardet, P., Collet, P., Lutton, E., Schoenauer, M. (eds) Artificial Evolution. EA 2005. Lecture Notes in Computer Science, vol 3871. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11740698_14

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  • DOI: https://doi.org/10.1007/11740698_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-33589-4

  • Online ISBN: 978-3-540-33590-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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