def benchmark_differential_evolution():
island = pg_island(algo=de(gen=10), prob=problem(rosenbrock(5)), size=10)
N = 10
print('Differential Evolution (pop. size {})'.format(
island.get_population().get_f().size))
for k in range(N):
island.evolve()
island.wait()
d = sqrt(
float(((island.get_population().champion_x -
rosenbrock(5).best_known())**2).mean()))
print('DE {:2}/{}: best fitness {:9.2f}, deviation {:9.2f}, fevals {}'.
format(k, N, float(island.get_population().champion_f[0]), d,
island.get_population().problem.get_fevals()))
def benchmark_simulated_annealing():
island = pg_island(algo=simulated_annealing(Ts=1., Tf=.01),
prob=problem(rosenbrock(5)),
size=10)
N = 10
print('Simulated Annealing (pop. size {})'.format(
island.get_population().get_f().size))
for k in range(N):
island.evolve()
island.wait()
d = sqrt(
float(((island.get_population().champion_x -
rosenbrock(5).best_known())**2).mean()))
print('SA {:2}/{}: best fitness {:9.2f}, deviation {:9.2f}, fevals {}'.
format(k, N, float(island.get_population().champion_f[0]), d,
island.get_population().problem.get_fevals()))
def benchmark_differential_evolution(generations):
island = pg_island(
algo=de(gen=generations),
prob=B2_UDP(getLowerBound(),getUpperBound(),'../../../../../sbml/b2.xml'),
size=10)
N = 50
import arrow
time_start = arrow.utcnow()
print('Differential Evolution (pop. size {})'.format(island.get_population().get_f().size))
for k in range(N):
island.evolve()
island.wait()
delta_t = arrow.utcnow() - time_start
print('DE {:2}/{}: best fitness {:9.2f}, fevals {}, duration {}'.format(
k,N,float(island.get_population().champion_f[0]),
island.get_population().problem.get_fevals(),
delta_t))
def benchmark_simulated_annealing():
island = pg_island(
algo=simulated_annealing(Ts=1.,Tf=.01),
prob=problem(B2_UDP(getLowerBound(),getUpperBound(),'../../../../../sbml/b2.xml')),
size=10)
N = 10
import arrow
time_start = arrow.utcnow()
print('Simulated Annealing (pop. size {})'.format(island.get_population().get_f().size))
for k in range(N):
island.evolve()
island.wait()
delta_t = arrow.utcnow() - time_start
print('SA {:2}/{}: best fitness {:9.2f}, fevals {}, duration {}'.format(
k,N,float(island.get_population().champion_f[0]),
island.get_population().problem.get_fevals(),
delta_t))