def main():
problema = rosenbrock.Rosenbrock()
problema_nombre = "rosenbrock"
cantidadParticulas = 50
iteraciones = 2000
dimensiones = 2
for dim in range(4):
for i in range(5):
de = DifferentialEvolution.DE(iteraciones, cantidadParticulas,
dimensiones, problema,
problema_nombre, i)
de.run()
dimensiones = dimensiones * 2
def main():
ros = rosenbrock.Rosenbrock()
individuos = 32
dimensiones = [2, 4, 8, 16]
intervalos = 8
a = 1
Q = 20
evaporacion = 0.9
t0 = 0.00001
generaciones = 2000
for dim in dimensiones:
for i in range(5):
aco = ACO.ACO(i, individuos, dim, intervalos, a, Q, evaporacion,
t0, ros, generaciones)
aco.run()
def main():
ros = rosenbrock.Rosenbrock()
sph = sphere.Sphere()
qua = quartic.Quartic()
ras = rastrigin.Rastrigin()
aux = np.array([])
graph = np.array([])
ejecuciones = 1
draw = drawer.Drawer()
individuos = 32
dimensiones = 16
intervalos = 8
a = 1
Q = 20
evaporacion = 0.9
t0 = 0.00001
generaciones = 100
bestFitnessPos = 100
graphName = "Quartic" + str(dimensiones) + "D"
aco = ACO.ACO(individuos, dimensiones, intervalos, a, Q, evaporacion, t0,
ras, generaciones, bestFitnessPos)
for i in range(ejecuciones):
aux = aco.run()
if i == 0:
graph = aux
else: #Sumamos el resto de las ejecuciones.
for a in range(len(aux)):
graph[a] = graph[a] + aux[a]
for x in range(len(graph)):
graph[x] = graph[
x] / ejecuciones #Obtenemos el promedio de cada posicion
draw.drawIndividual(graph, graphName)
file = open(graphName + ".txt", "w")
for y in range(len(graph)):
file.write(str(graph[y]) + "\n")
file.close()
def main():
problema = rosenbrock.Rosenbrock()
problema_nombre = "rosenbrock"
cantidadParticulas = 50
tamanioVecindario = 16
iteraciones = 2000
dimensiones = 2
cognitionLearningRate = 1.4944
socialLearningRate = 1.4944
for dim in range(4):
for i in range(5):
spo = SwarmParticleOptimization.SPO(iteraciones,
cantidadParticulas,
tamanioVecindario, dimensiones,
cognitionLearningRate,
socialLearningRate, problema,
problema_nombre, i)
spo.run()
dimensiones = dimensiones * 2
def main():
sphere_problem = sphere.Sphere()
rastrigin_problem = rastrigin.Rastrigin()
quartic_problem = quartic.Quartic()
rosenbrock_problem = rosenbrock.Rosenbrock()
population_size = 16
generations = 2000
mutation_rate = 0.1
for dimentions in [2, 4, 8]:
raw_sets = []
for i in range(5):
ag = PSAlgorithm.ParticleSwarmAlgorithm(population_size, dimentions, generations, mutation_rate, quartic_problem)
raw_sets.append(ag.run())
print(zip_average(raw_sets), dimentions)
plt.plot(range(100, generations+100, 100), zip_average(raw_sets), label = str(dimentions))
# plt.legend(['2', '4', '8'])
plt.legend()
plt.show()
def main():
rosen = rosenbrock.Rosenbrock()
rango = rosen.MAX_VALUE - rosen.MIN_VALUE
cantidad_individuos = 30