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I'm having an issue of execution perfomance and I can't figure it out why.
For testing purposes I have set 40 generations and is taking about a minute
to end. 4000 generations elapsed time is about an hour.

In order to determine the cause of the problem I have set crossover and
mutation probabilty to 0 and the problem persists, so that I assume is
something on ECJ execution.

Someone can help me?

I have two objetives, one of them maximization and the other minimization.
In fitness function I set fitness the inverse function (objectives[1] =
(-1)*fitness2). Crossover and mutation as custom functions.

Here is my params file:

parent.0 = ../moosuite/moosuite.params
eval.problem = ec.app.MyProblem.MyProblem

evalthreads = 2
generations = 4000
quit-on-run-complete = true

stat = ec.multiobjective.MultiObjectiveStatistics
stat.file = $out.stat

pop = ec.Population
pop.subpops   = 1
pop.subpop.0 = ec.Subpopulation
pop.subpop.0.size = 50

pop.subpop.0.species = ec.vector.GeneVectorSpecies
pop.subpop.0.species.ind = ec.vector.GeneVectorIndividual
pop.subpop.0.species.gene = ec.app.MyGene.MyGene

pop.subpop.0.species.fitness.num-objectives = 2
pop.subpop.0.species.fitness.maximize = true

pop.subpop.0.species.crossover-type = one
pop.subpop.0.species.mutation-type = reset
pop.subpop.0.species.mutation-prob = 0.05

pop.subpop.0.species.pipe     = ec.vector.breed.VectorMutationPipeline
pop.subpop.0.species.pipe.likelihood         = 1.0
pop.subpop.0.species.pipe.source.0 = ec.vector.breed.VectorCrossoverPipeline
pop.subpop.0.species.pipe.source.0.likelihood = 0.6
pop.subpop.0.species.pipe.source.0.source.0 = ec.select.TournamentSelection
pop.subpop.0.species.pipe.source.0.source.1 = same
select.tournament.size = 2

seed.0 = time
seed.1 = time