The use of genetic algorithms in the optimization of competitive neural networks which resolve the stuck vectors problem

We show that for variable rates of mutation and crossover that depend on the global fitness of the population, and selection of reproduction pair that is asymmetric, solutions to problems with stringent constraints are found.