from libs.LerArquivo import LerArquivo
from libs.Particula import Particula
from libs.Graph import Graph
MAX_ITERACOES = 1000
NUM_PARTICLES = 100
if __name__ == "__main__":
import copy
fuckingBestFit = 1e9
veiculos = None
numClientes, capacidade, coords, demandas, timeWindow, matrizDistancia = LerArquivo().readFile("In/TW/25C/C101.txt")
particulas = [Particula(numClientes, capacidade, coords, demandas, timeWindow, matrizDistancia) for _ in range(NUM_PARTICLES)]
try:
codificacao = None
for particula in particulas:
if(particula.fitness < fuckingBestFit):
fuckingBestFit = particula.fitness
codificacao = copy.deepcopy(particula.posicao)
for i in range(NUM_PARTICLES):
particulas[i].gbest = copy.deepcopy(codificacao)
particulas[i].fitness = fuckingBestFit
# print(p.posicao - p.gbest)
atualizou = False
for iteracao in range(MAX_ITERACOES):
# print("Iteracao #{}: {:.5f}".format(iteracao, particulas[0].fitness))
atualizou = False
for i in range(NUM_PARTICLES):
fitness = particulas[i].calculaFitness()
if(fitness < particulas[i].fitness):
particulas[i].fitness = fitness
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