Hello, I'm working with a GA problem. For this I implemented the Gene and the GeneVectorIndividual. I also had to override the crossover and mutation methods. The weird of the algorithm behave is that if I set the mutation-prob value different of zero my population don't evolve and the best individuals present on the final chart pdf in each generation are very oscillate (see Mutation.pdf attached). In the other way, if I put the mutation-prob to zero, the population are evolve gradually, but this evolution is little and more stable, because don't occurs mutation (see Crossover-Any.pdf attached). Anyone know what is occurs and how do I fix it? It seems that after mutate process, the parents (fittest of the population) of the clones are not put in the new Subpopulation then next generations never evoluate. My main params: pop.subpop.0.species.crossover-prob = 0.25 pop.subpop.0.species.crossover-type = any base.likelihood = 0.5 pop.subpop.0.species.mutation-prob = 0.1 pop.subpop.0.species.pipe = ec.vector.breed.VectorMutationPipeline pop.subpop.0.species.pipe.source.0 = ec.vector.breed.VectorCrossoverPipeline pop.subpop.0.species.pipe.source.0.source.0 = ec.select.TournamentSelection pop.subpop.0.species.pipe.source.0.source.1 = ec.select.TournamentSelection select.tournament.size = 2 Best Regards, Victor jatobá