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This study concerns with the Boolean satisfiability (SAT) prolem and its solution in the setting of a hybrid computational intelligence environment of genetic and fzzy computing. In this tramework, fuzzy sets realize an embedding principle meaning that original two-values (Boolean) fubctions under investigation are extended to their continuous counterparts resulting in the form of fuzzy (multivalued) functions. In the sequel, the satisfiability 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.
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Operational Program Digital Poland, 2014-2020, Measure 2.3: Digital accessibility and usefulness of public sector information; funds from the European Regional Development Fund and national co-financing from the state budget.
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