def crossover(self, pcross):
for i in xrange(0, self.pop_size, 2):
if random() < pcross:
(son1, son2) = Crossovers.single_point_crossover(self.internal_pop[i], self.internal_pop[i+1])
self.internal_pop[i] = son1
self.internal_pop[i].needs_eval = True
self.internal_pop[i+1] = son2
self.internal_pop[i+1].needs_eval = True
def cruzar_y_mutar(rutaparticula, rutavecino, opcross, opmut):
# Por defecto se realizará un crossover Order1 y no mutacion
if opcross == 1: # Order1
nuevaruta = Crossovers.Order1(rutaparticula, rutavecino)
elif opcross == 2: # Cycle
nuevaruta = Crossovers.Cycle(rutaparticula, rutavecino)
elif opcross == 3: # Partially mapped crossover
nuevaruta = Crossovers.PMX(rutaparticula, rutavecino)
else: # Si no es numero de operador valido, se realizar un Order1
nuevaruta = Crossovers.Order1(rutaparticula, rutavecino)
# Mutaciones. Por defecto no se realizará la operacion de mutacion
# Hay un 10% de probabilidades de realizar una mutacion
if random.randint(0, 100) < 15:
if opmut == 1: # Inversion
nuevaruta = Mutations.Inversion(nuevaruta)
elif opmut == 2: # SingleSwap
nuevaruta = Mutations.RandomSwap(nuevaruta)
return nuevaruta
#import Mutators
import time
if __name__ == "__main__":
size = 100
cross_max_iters = 100000
#mut_max_iters = 1000000
pmut = 0.02
dad = BinaryString.BinaryString(size)
mom = BinaryString.BinaryString(size)
#print dad
#print mom
start = time.time()
for i in xrange(1, cross_max_iters):
(son1, son2) = Crossovers.single_point_crossover(dad, mom)
end = time.time()
print "single_point_crossover time:", ((end-start)*1000) / cross_max_iters, "ms"
#print son1
#print son2
start = time.time()
for i in xrange(1, cross_max_iters):
(son1, son2) = Crossovers.two_point_crossover(dad, mom)
end = time.time()
print "two_point_crossover time:", ((end-start)*1000) / cross_max_iters, "ms"
start = time.time()
for i in xrange(1, cross_max_iters):
(son1, son2) = Crossovers.uniform_crossover(dad, mom)
