Title :
Genetic-fuzzy approach to the Boolean satisfiability problem
Author :
Pedrycz, Witold ; Succi, Giancarlo ; Shai, Ofer
Author_Institution :
Dept. of Electr. & Comput. Eng., Alberta Univ., Edmonton, Alta., Canada
fDate :
10/1/2002 12:00:00 AM
Abstract :
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
Keywords :
Boolean functions; computability; fuzzy logic; fuzzy set theory; genetic algorithms; Boolean functions; Boolean satisfiability problem; embedding principle; experiments; fuzzy computing; fuzzy multivalued functions; fuzzy sets; genetic algorithms; genetic-fuzzy approach; hybrid computational intelligence environment; triangular norms; two-valued functions; Application software; Automatic testing; Boolean functions; Computational intelligence; Explosions; Fuzzy sets; Genetic algorithms; Logic; NP-complete problem; System testing;
Journal_Title :
Evolutionary Computation, IEEE Transactions on
DOI :
10.1109/TEVC.2002.804915