def cross(self, p1, p2):
logger.debug("Crossing: " + str(p1) + " and " + str(p2))
parent1 = p1.list[:]
parent2 = p2.list[:]
index1 = random.randrange(0, len(parent1))
index2 = random.randrange(0, len(parent1))
if index1 > index2:
tmp = index1
index1 = index2
index2 = tmp
parent1fragment = parent1[index1:index2]
parent2fragment = parent2
for city in parent1fragment:
parent2fragment.remove(city)
genlist = parent1fragment + parent2fragment
genotype = TSPGenotype(p1.cities)
genotype.set_list(genlist)
logger.debug("Crossed genotype: " + str(genotype))
return genotype
def __call__(self):
agents = {}
for i in range(self.size):
agent = EmasAgent(TSPGenotype(self.cities), self.energy,
self.naming_service.get_next_agent())
agents[agent.get_address()] = agent
return agents
def mutate(self, genotype):
logger.debug("Inverse mutation of {0}".format(str(genotype)))
new_gen = TSPGenotype(genotype.points, order=inverse(genotype.order))
logger.debug("Mutated {0}".format(str(new_gen)))
return new_gen
def mutate(self, genotype):
logger.debug("Mutating (next swap) genotype: " + str(genotype))
l = genotype.list[:]
index1 = random.randrange(0, len(l))
index2 = (index1 + 1) % len(l)
e1 = l[index1]
e2 = l[index2]
l[index2] = e1
l[index1] = e2
gen = TSPGenotype(genotype.cities)
gen.set_list(l)
logger.debug("Mutated (next swap) genotype: " + str(gen))
return gen
def mutate(self, genotype):
logger.debug("Mutating (next swap) genotype: " + str(genotype))
l = genotype.list[:]
index1 = random.randrange(0, len(l))
index2 = (index1 + 1) % len(l)
e1 = l[index1]
e2 = l[index2]
l[index2] = e1
l[index1] = e2
gen = TSPGenotype(genotype.cities)
gen.set_list(l)
logger.debug("Mutated (next swap) genotype: " + str(gen))
return gen
def __init__(self, population_size=1000, filename=None):
super(TSPInitializer, self).__init__(TSPGenotype)
self.size = population_size
if filename:
self.points = initialize_points(filename)
self.population = [
TSPGenotype(self.points) for _ in range(self.size)
]
def mutate(self, genotype):
logger.debug("Consecutive mutation of {0}".format(str(genotype)))
n = len(genotype.order)
random_choice = random.randrange(n)
new_gen = TSPGenotype(genotype.points,
order=swap(list(genotype.order), random_choice,
(random_choice + 1) % n))
logger.debug("Mutated {0}".format(str(new_gen)))
return new_gen
def mutate(self, genotype):
logger.debug("Random mutation of {0}".format(str(genotype)))
n = len(genotype.order)
new_gen = TSPGenotype(genotype.points,
order=swap(list(genotype.order),
random.randrange(n),
random.randrange(n)))
logger.debug("Mutated {0}".format(str(new_gen)))
return new_gen
def cross(self, p1, p2):
logger.debug("Crossing {0} and {1}".format(str(p1), str(p2)))
p1_order = list(p1.order)
p2_order = list(p2.order)
points_size = len(p1_order)
l = random.randrange(0, points_size)
r = random.randrange(0, points_size)
if l > r:
l, r = r, l
parent1_order_part = p1_order[l:r]
for city in parent1_order_part:
p2_order.remove(city)
genotype = TSPGenotype(p1.points, order=parent1_order_part + p2_order)
logger.debug("Crossed: {0}".format(str(genotype)))
return genotype
def generate_population(self, number_of_genotypes, cities):
return [TSPGenotype(cities) for _ in xrange(0, number_of_genotypes)]