Parallel Hybrid Method for SAT that Couples Genetic Algorithms and Local Search

A parallel hybrid method for solving the satisfiability
(SAT) problem that combines cellular genetic algorithms
(GAs) and the random walk SAT (WSAT) strategy of greedy
SAT (GSAT) is presented. The method, called cellular genetic
WSAT (CGWSAT), uses a cellular GA to perform a global search
from a random initial population of candidate solutions and a
local selective generation of new strings. Global search is then
specialized in local search by adopting the WSAT strategy. A main
characteristic of the method is that it indirectly provides a parallel
implementation of WSAT when the probability of crossover is
set to zero. CGWSAT has been implemented on a Meiko CS-2
parallel machine using a two-dimensional cellular automaton as
a parallel computation model. The algorithm has been tested on
randomly generated problems and some classes of problems from
the DIMACS and SATLIB test set.