def main():
sims = [('max', MyChromoPos), ('min', MyChromoPos), ('max', MyChromoNeg),
('min', MyChromoNeg)]
for s in sims:
print(s)
ga = GenAlg(
size=10,
elitism=0.10,
crossover=0.60,
pureMutation=0.30,
parentsPct=0.80,
chromoClass=s[1],
#selectionFcn = GenAlgOps.tournamentSelection,
#crossoverFcn = GenAlgOps.crossover22,
#mutationFcn = GenAlgOps.mutateFew,
#pureMutationSelectionFcn = GenAlgOps.simpleSelection,
#pureMutationFcn = GenAlgOps.mutateFew,
#feasibleSolnFcn = GenAlgOps.disallowDupes,
minOrMax=s[0],
showBest=0,
)
ga.initPopulation()
for i in range(10):
if (s[1] == MyChromoNeg):
ga.population[i].data[0] = -i - 1
else:
ga.population[i].data[0] = i + 1
ga.calcFitness()
ga.sortPopulation()
printGaPopulation(ga)
counts = [0 for i in range(10)]
for i in range(10000):
idx1, idx2 = GenAlgOps.rouletteWheelSelection(ga)
counts[idx1] = counts[idx1] + 1
counts[idx2] = counts[idx2] + 1
print(' roulette counts = ' + str(counts))
counts = [0 for i in range(10)]
for i in range(10000):
idx1, idx2 = GenAlgOps.rankSelection(ga)
counts[idx1] = counts[idx1] + 1
counts[idx2] = counts[idx2] + 1
print(' rank counts = ' + str(counts))
def main():
ga = GenAlg(
size=10,
elitism=0.10,
crossover=0.60,
pureMutation=0.30,
parentsPct=0.80,
chromoClass=MyChromo,
#selectionFcn = GenAlgOps.tournamentSelection,
#crossoverFcn = GenAlgOps.crossover22,
#mutationFcn = GenAlgOps.mutateFew,
#pureMutationSelectionFcn = GenAlgOps.simpleSelection,
#pureMutationFcn = GenAlgOps.mutateFew,
feasibleSolnFcn=GenAlgOps.disallowDupes,
minOrMax='max',
showBest=0,
)
ga.initPopulation()
ga.calcFitness()
child = MyChromo()
child.data[0] = ga.population[4].data[0]
child.fitness = ga.population[4].fitness
feas = GenAlgOps.disallowDupes(ga, child)
print('unsorted population; data present; feas=', feas)
child.data[0] = ga.population[4].data[0] + 9
child.fitness = ga.population[4].fitness + 9
feas = GenAlgOps.disallowDupes(ga, child)
print('unsorted population; data not present; feas=', feas)
ga.sortPopulation()
child.data[0] = ga.population[4].data[0]
child.fitness = ga.population[4].fitness
feas = GenAlgOps.disallowDupes(ga, child)
print('sorted population; data at pos=4; feas=', feas)
child.data[0] = ga.population[4].data[0] + 9
child.fitness = ga.population[4].fitness + 9
feas = GenAlgOps.disallowDupes(ga, child)
print('sorted population; data not present; feas=', feas)