PFGASAT" A Genetic SAT Solver Combining Partitioning and Fuzzy Strategies
COMPSAC '04 Proceedings of the 28th Annual International Computer Software and Applications Conference - Volume 01
Evolutionary algorithms for reasoning in fuzzy description logics with fuzzy quantifiers
Proceedings of the 9th annual conference on Genetic and evolutionary computation
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This study is concerned with the Boolean satisfiability (SAT) problem and its solution in setting a hybrid computational intelligence environment of genetic and fuzzy computing. In this framework, fuzzy sets realize an embedding principle meaning that original two-valued (Boolean) functions under investigation are extended to their continuous counterparts resulting in the form of fuzzy (multivalued) functions. In the sequel, the SAT problem is reformulated for the fuzzy functions and solved using a genetic algorithm (GA). It is shown that a GA, especially its recursive version, is an efficient tool for handling multivariable SAT problems. Thorough experiments revealed that the recursive version of the GA can solve SAT problems with more than 1000 variables