GASAT: A Genetic Local Search Algorithm for the Satisfiability Problem

This paper presents GASAT, a hybrid algorithm for the satisfiability problem (SAT). The main feature of GASAT is that it includes a recombination stage based on a specific crossover and a tabu search stage. We have conducted experiments to evaluate the different components of GASAT and to compare it...

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Bibliographic Details
Published inEvolutionary computation Vol. 14; no. 2; pp. 223 - 253
Main Authors Lardeux, Frédéric, Saubion, Frédéric, Hao, Jin-Kao
Format Journal Article
LanguageEnglish
Published One Rogers Street, Cambridge, MA 02142-1209, USA MIT Press 01.06.2006
Massachusetts Institute of Technology Press (MIT Press)
Subjects
Algorithms
Artificial Intelligence
Computational Biology - methods
Computer Science
Computer Simulation
Evolution, Molecular
evolutionary algorithms
Humans
Models, Genetic
Models, Statistical
Models, Theoretical
Pattern Recognition, Automated
Programming Languages
recombination operators
SAT
Software
tabu search
tabu search
recombination operators
SAT
evolutionary algorithms
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Summary:This paper presents GASAT, a hybrid algorithm for the satisfiability problem (SAT). The main feature of GASAT is that it includes a recombination stage based on a specific crossover and a tabu search stage. We have conducted experiments to evaluate the different components of GASAT and to compare its overall performance with state-of-the-art SAT algorithms. These experiments show that GASAT provides very competitive results.
Bibliography:Summer, 2006
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ISSN:1063-6560
1530-9304
DOI:10.1162/evco.2006.14.2.223