w = 0
for i, _ in enumerate(x):
w = w + (x[i] * W[i])
# penalizo sobrepasar el peso maximo
return c if w <= M else 0
o = BCSO(test_function,
dimension=N,
maxiter=150,
maximize=True,
workers=1,
threads=1,
cats=500,
mr=0.5,
smp=20,
cdc=0.7,
pmo=0.7,
spc=False,
omega=0.5,
weight=1)
best = o.run()
print(best[BCSO.BEST_FUNC_TEST_VALUE])
decode = []
for i, x in enumerate(best[BCSO.BEST_CAT_POSITION]):
if x:
for j, _ in enumerate(x):
n = n + (matrix[i][j] * x[j])
if n == 0:
c = c + 100000
return c
o = BCSO(test_function,
dimension=n_group,
maxiter=12,
workers=1,
threads=1,
cats=100,
mr=0.5,
smp=10,
cdc=0.5,
pmo=0.1,
spc=False,
omega=0.5,
weight=1,
debug=False)
best = o.run()
print(best[BCSO.BEST_FUNC_TEST_VALUE])
decode_covering = []
for i, x in enumerate(best[BCSO.BEST_CAT_POSITION]):
if x:
for j, _ in enumerate(x):
n = n + (matrix[i][j] * x[j])
if n == 0:
c = c + 1000
return c
o = BCSO(test_function,
dimension=n_group,
maxiter=300,
workers=1,
threads=1,
cats=150,
mr=0.5,
smp=20,
cdc=0.7,
pmo=0.1,
spc=False,
omega=0.5,
weight=1)
best = o.run()
print(best[BCSO.BEST_FUNC_TEST_VALUE])
decode_covering = []
for i, x in enumerate(best[BCSO.BEST_CAT_POSITION]):
if x:
from cso import BCSO
dataset = [10, -10, 20, 1, 3, 25, -100, 20]
def test_function(x, *args, **kwargs):
c = 0
for i, f in enumerate(x):
if f == 1:
c = c + dataset[i]
return c
omin = BCSO(test_function,
dimension=len(dataset), maximize=False, n_cats=100, smp=10, maxiter=100, cdc=1, mr=0.5)
omax = BCSO(test_function,
dimension=len(dataset), maximize=True, n_cats=100, smp=10, maxiter=100, cdc=1, mr=0.5)
best_min = omin.run()
best_max = omax.run()
print(dataset)
print()
print('min', best_min)
print()
print('max', best_max)