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 

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 =
pop.subpop.0.species.pipe.source.0.source.1 =

select.tournament.size = 2

Best Regards,
Victor jatobá