# Copyright 2006 by Sean Luke and George Mason University
# Licensed under the Academic Free License version 3.0
# See the file "LICENSE" for more information

parent.0 = ../../simple/simple.params

# The following is a quick-and-dirty example of how to use the vector
# package to create a simple GA.  The GA is as follows:
#
# 1-point crossover over a vector of integers
# ints range from 0 to 100 inclusive.  Fitness = sum(vector)
# 2-tournament selection
# Individuals are selected, crossed over, and then mutated
# mutation probability = 0.1
# mutation is randomization of the integer

pop.subpop.0.size = 10
generations = 20000 

pop.subpop.0.duplicate-retries = 0

# specify species information
pop.subpop.0.species = 			ec.vector.IntegerVectorSpecies
pop.subpop.0.species.fitness =		ec.simple.SimpleFitness
pop.subpop.0.species.ind = 		ec.vector.IntegerVectorIndividual
pop.subpop.0.species.min-gene = 0
pop.subpop.0.species.max-gene = 100
pop.subpop.0.species.genome-size = 10
pop.subpop.0.species.crossover-type = one
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

select.tournament.size = 2
pop.subpop.0.species.pipe.source.0.source.0 = ec.select.TournamentSelection
pop.subpop.0.species.pipe.source.0.source.1 = same

eval.problem = ec.app.sum.Sum