def main():
global NUM_PARTICLES, GBEST
# try:
NUM_ITERACOES = 1000
num_Clientes = 25 if (len(sys.argv) == 1) else int(sys.argv[1])
num_Arquivo = int(sys.argv[2])
NUM_PARTICLES = 100
# print(num_Clientes, num_Arquivo)
num_Veiculos, veiculos_Capacidades, coords, demandas, coletas, time_Window, matriz_Distancia = LerArquivo(
).readFile("../entry-{}".format(num_Arquivo), num_Clientes)
clientes = []
for i in range(num_Clientes):
clientes.append(
Cliente(coords[i + 1], i + 1, demandas[i + 1], coletas[i + 1],
time_Window[i + 1]))
Global.init(num_Veiculos, num_Clientes, veiculos_Capacidades, coords,
demandas, coletas, time_Window, matriz_Distancia, clientes,
NUM_PARTICLES, NUM_ITERACOES)
particles = []
for i in range(Global.NUM_PARTICLES):
particles.append(Particle())
GBEST = get_GBest(particles)
for i in range(Global.NUM_PARTICLES):
particles[i].set_GBest(GBEST)
# print("Fitness atual: {}".format(GBEST.fitness))
for itera in range(Global.NUM_ITERACOES):
update = False
for i in range(Global.NUM_PARTICLES):
particles[i].update_Velocidade(itera)
particles[i].update_Posicao()
update = update or particles[i].update()
if (update):
GBEST = get_GBest(particles)
for i in range(Global.NUM_PARTICLES):
particles[i].set_GBest(GBEST)
# print("Iteracao #{}".format(itera))
# print("Melhor fitness: {}".format(particles[0].gbest.fitness))
# finally:
# # for l in GBEST.rotas:
# # print(' '.join([str(x.id) for x in l.clientes]))
# Graph().draw(GBEST.rotas)
print(GBEST.fitness)
def main():
global NUM_PARTICLES, GBEST
NUM_ITERACOES = 1000
num_Clientes = 25
NUM_PARTICLES = num_Clientes
num_Veiculos, capacidade, coords, demandas, time_Window, matriz_Distancia = LerArquivo(
).readFile("In/TW/{}C/C101.txt".format(num_Clientes), num_Clientes)
clientes = []
for i in range(num_Clientes):
clientes.append(
Cliente(coords[i + 1], i + 1, demandas[i + 1], time_Window[i + 1]))
Global.init(num_Veiculos, num_Clientes, capacidade, coords, demandas,
time_Window, matriz_Distancia, clientes, NUM_PARTICLES,
NUM_ITERACOES)
particles = []
for i in range(Global.NUM_PARTICLES):
particles.append(Particle())
GBEST = get_GBest(particles)
for i in range(Global.NUM_PARTICLES):
particles[i].set_GBest(GBEST)
for itera in range(Global.NUM_ITERACOES):
update = False
for i in range(Global.NUM_PARTICLES):
particles[i].update_Velocidade(itera)
particles[i].update_Posicao()
update = update or particles[i].update()
if (update):
GBEST = get_GBest(particles)
for i in range(Global.NUM_PARTICLES):
particles[i].set_GBest(GBEST)
print("Iteracao #{}".format(itera))
print("Melhor fitness: {}".format(particles[0].gbest.fitness))
# for i, particle in enumerate(particles):
# vel_Veiculo = particle.vel[Global.num_Clientes:]
# print("Particle #{} = {}".format(i + 1, vel_Veiculo))
Graph().draw(GBEST.rotas)
def main():
global NUM_PARTICLES, GBEST, tot
tot = 0
NUM_ITERACOES = 100
num_Clientes = 25 if (len(sys.argv) == 1) else int(sys.argv[1])
for _ in range(5):
NUM_PARTICLES = 50
num_Veiculos, capacidade, coords, demandas, coletas, time_Window, matriz_Distancia = LerArquivo(
).readFile("In/TWSPD/{}C/IC102.txt".format(num_Clientes), num_Clientes)
clientes = []
for i in range(num_Clientes):
clientes.append(
Cliente(coords[i + 1], i + 1, demandas[i + 1], coletas[i + 1],
time_Window[i + 1]))
Global.init(num_Veiculos, num_Clientes, capacidade, coords, demandas,
coletas, time_Window, matriz_Distancia, clientes,
NUM_PARTICLES, NUM_ITERACOES)
particles = []
for i in range(Global.NUM_PARTICLES):
particles.append(Particle())
GBEST = get_GBest(particles)
for i in range(Global.NUM_PARTICLES):
particles[i].set_GBest(GBEST)
for itera in range(Global.NUM_ITERACOES):
update = False
for i in range(Global.NUM_PARTICLES):
particles[i].update_Velocidade(itera)
particles[i].update_Posicao()
update = update or particles[i].update()
if (update):
GBEST = get_GBest(particles)
for i in range(Global.NUM_PARTICLES):
particles[i].set_GBest(GBEST)
print("Melhor fitness #{}: {}".format(
itera, particles[0].gbest.fitness))
print("Melhor fitness: {}".format(particles[0].gbest.fitness))
tot += particles[0].gbest.fitness
def main():
global NUM_PARTICLES, GBEST
NUM_ITERACOES = 1000
num_Clientes = 100
NUM_PARTICLES = 100
pastas = ["C101_Het_FC_0.95"]
valores = [(0.95, 2.85)]
# try:
for (pasta, valor) in zip(pastas, valores):
for arq in range(0, 11):
with open("{}/{}_{}.txt".format(pasta, pasta, arq), "w") as file:
num_Veiculos, veiculos_Capacidades, coords, demandas, coletas, time_Window, matriz_Distancia = LerArquivo().readFile("In/TWSPD/{}C/IC101.txt".format(num_Clientes), num_Clientes)
clientes = []
for i in range(num_Clientes):
clientes.append(Cliente(coords[i + 1], i + 1, demandas[i + 1], coletas[i + 1], time_Window[i + 1]))
Global.init(num_Veiculos, num_Clientes, veiculos_Capacidades, coords, demandas, coletas, time_Window, matriz_Distancia, clientes, NUM_PARTICLES, NUM_ITERACOES)
particles = []
for i in range(Global.NUM_PARTICLES):
particles.append(Particle(1.0, valor[0], valor[1]))
GBEST = get_GBest(particles)
for i in range(Global.NUM_PARTICLES):
particles[i].set_GBest(GBEST)
print("Fitness atual: {}".format(GBEST.fitness))
anterior = -1
contador = 0
for itera in range(Global.NUM_ITERACOES):
update = False
for i in range(Global.NUM_PARTICLES):
particles[i].update_Velocidade(itera)
particles[i].update_Posicao()
temp_inicial = 10.0
temp_final = 0.0000001
A = 1 / (float(NUM_ITERACOES)) * math.log(temp_inicial / temp_final)
t_atual = temp_inicial * math.exp(-A * (itera + 1))
mapeado = t_atual / 10.0
# print(itera, mapeado)
update = update or particles[i].update(-1)
if(update):
GBEST = get_GBest(particles)
for i in range(Global.NUM_PARTICLES):
particles[i].set_GBest(GBEST)
qtd_Veiculos = sum([1 for x in GBEST.rotas if len(x.clientes) > 2])
file.write(str(itera) + ":" + str(particles[0].gbest.fitness) + ":" + str(qtd_Veiculos) + "\n")
print("Iteracao #{}: {} com {} veiculos".format(itera, particles[0].gbest.fitness, qtd_Veiculos))
if(particles[0].gbest.fitness <= 829.0):
break
if(particles[0].gbest.fitness == anterior):
contador += 1
if(contador >= 200):
particles = []
contador = 0
for i in range(Global.NUM_PARTICLES):
particles.append(Particle(1.0))
GBEST = get_GBest(particles)
for i in range(Global.NUM_PARTICLES):
particles[i].set_GBest(GBEST)
else:
contador = 0
anterior = particles[0].gbest.fitness