Using Neutral Networks and Genetic Algorithms as Heuristics for NP-complete Problems

Paradigms for using neural networks (NNs) and genetic algorithms (GAs) to heuristicaJIy solve boolean satisfiability (SAT) problems are presented. Since SAT is NP-Complete, any olher NP-Compleie problem can be transformed into an equivalent SAT problem in polynomial Lime, and solved via either paradigm. This technique is illustrated for hamiltonian circuit (HC) problems.