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An Evolutionary Local Search Algorithm for the Satisfiability Problem

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Artificial Intelligence and Neural Networks (TAINN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3949))

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Abstract

Satisfiability problem is an NP-complete problem that finds itself or its variants in many combinatorial problems. There exist many complete algorithms that give successful results on hard problems, but they may be time-consuming because of their branch and bound structures. In this manner, many successful incomplete algorithms are introduced. In this paper, the improvement of incomplete algorithms is of interest and it is shown that the incomplete algorithms can be more efficient if they are equipped with the problem specific knowledge, goal-oriented operators, and knowledge-based methods. In this aspect, an evolutionary local search algorithm is implemented, tested on a randomly generated benchmark that includes test instances with different sizes, and compared with prominent incomplete algorithms. Also, effects of goal-oriented genetic operators and knowledge-based methods used in the evolution-ary local search algorithm are examined by making comparisons with blind operators and random methods.

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Author information

Authors and Affiliations

  1. Faculty of Electrical and Electronics Engineering Department of Electronics and Communication Engineering, Istanbul Technical University, 34469, Maslak, Istanbul, Turkey

    Levent Aksoy & Ece Olcay Gunes

Authors
  1. Levent Aksoy
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  2. Ece Olcay Gunes
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Editor information

Editors and Affiliations

  1. Izmir Institute of Technology, Electrical Electronics Engineering, Gülbahçe, Urla, Izmir, Turkey

    F. Acar Savacı

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© 2006 Springer-Verlag Berlin Heidelberg

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Aksoy, L., Gunes, E.O. (2006). An Evolutionary Local Search Algorithm for the Satisfiability Problem. In: Savacı, F.A. (eds) Artificial Intelligence and Neural Networks. TAINN 2005. Lecture Notes in Computer Science(), vol 3949. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11803089_22

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  • DOI: https://doi.org/10.1007/11803089_22

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-36713-0

  • Online ISBN: 978-3-540-36861-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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