Using Neural Networks and Genetic Algorithms as Heuristics for NP-Complete Problems: M.Sc. thesis PDF
83 Pages·1989·0.163 MB·English
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Preview Using Neural Networks and Genetic Algorithms as Heuristics for NP-Complete Problems: M.Sc. thesis
Description:
Paradigms for using neural networks (NNs) and genetic algorithms (GAs) toheuristically solve boolean satisfiability (SAT) problems are presented. Resultsare presented for two-peak and false-peak SAT problems. Since SAT is NP-Complete,any other NP-Complete problem can be transformed into an equivalentSAT problem in polynomial time, and solved via either paradigm. This techniqueis illustrated for Hamiltonian circuit (HC) problems.
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