A novel method, for solving satisfiability (SAT) instances is presented. It is based on two components: a) An Epistasis Reducer Algorithm (ERA) that produces a more suited representation (with lower epistasis) for a Genetic Algorithm (GA) by preprocessing the original SAT problem; and b) A Genetic Algorithm that solves the preprocesed instances. ERA is implemented by a simulated annealing algorithm (SA), which transforms the original SAT problem by rearranging the variables to satisfy the condition that the most related ones are in closer positions inside the chromosome. Results of experimentation demonstrated that the proposed combined approach outperforms GA in all the tests accomplished.
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