Hopfield neural network and genetic algorithm, a comparison in the case of hierarchical graph visualization

We present the design of a Hopfield neural network and a genetic algorithm to solve the hierarchical graph visualization problem. Both are single phase algorithms and were developed to simultaneously minimize the number of crossings and the total path length. Results comparing the neural network and genetic algorithm are presented as well as a comparison to a traditional heuristic approach. Both the neural network and genetic algorithm were shown to provide high quality solutions in term of the readability criteria