Combinatorial Optimization with Neural Networks
A general introduction to the use of feed-back artificial neural networks (ANN) for obtaining good approximate solutions to combinatorial optimization problems is given, assuming no previous knowledge in the field. In particular we emphasize a novel neural mapping technique which efficiently reduces the solution space. This approach maps the problems onto Potts glass rather than spin glass models.