title: GASAT: a genetic local search algorithm for the satisfiability problem.
abstract: 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.
authors.affiliation: LERIA, University of Angers, F-49045 Angers Cedex, France. lardeux@info.univ-angers.fr
authors.forename: Frédéric
authors.initials: F
authors.lastname: Lardeux
authors.forename: Frédéric
authors.initials: F
authors.lastname: Saubion
authors.forename: Jin-Kao
authors.initials: JK
authors.lastname: Hao
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D019143:Evolution, Molecular; D006801:Humans; D008957:Models, Genetic; D015233:Models, Statistical; D008962:Models, Theoretical; D010363:Pattern Recognition, Automated; D011381:Programming Languages; D012984:Software