Evolutionary Computing for the Satisfiability Problem
Résumé
This paper presents GASAT, a hybrid evolutionary algorithm for the satisfiability problem (SAT). A specific crossover operator generates new solutions, that are improved by a tabu search procedure. The performance of GASAT is assessed using a set of well-known benchmarks. Comparisons with state-of-the-art SAT algorithms show that GASAT gives very competitive results. These experiments also allow us to introduce a new SAT benchmark from a coloring problem.
Domaines
Intelligence artificielle [cs.AI]
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Hao2003_Chapter_EvolutionaryComputingForTheSat.pdf (170.27 Ko)
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