def get_setup(n_obj):
if n_obj == 3:
pop_size = 92
ref_dirs = UniformReferenceDirectionFactory(n_obj, n_partitions=12).do()
elif n_obj == 5:
pop_size = 212
ref_dirs = UniformReferenceDirectionFactory(n_obj, n_partitions=6).do()
elif n_obj == 8:
pop_size = 156
ref_dirs = MultiLayerReferenceDirectionFactory([
UniformReferenceDirectionFactory(n_obj, n_partitions=3, scaling=1.0),
UniformReferenceDirectionFactory(n_obj, n_partitions=2, scaling=0.5)]).do()
elif n_obj == 10:
pop_size = 276
ref_dirs = MultiLayerReferenceDirectionFactory([
UniformReferenceDirectionFactory(n_obj, n_partitions=3, scaling=1.0),
UniformReferenceDirectionFactory(n_obj, n_partitions=2, scaling=0.5)]).do()
elif n_obj == 15:
pop_size = 136
ref_dirs = MultiLayerReferenceDirectionFactory([
UniformReferenceDirectionFactory(n_obj, n_partitions=2, scaling=1.0),
UniformReferenceDirectionFactory(n_obj, n_partitions=1, scaling=0.5)]).do()
return {
'ref_dirs': ref_dirs,
'pop_size': pop_size,
'crossover': SimulatedBinaryCrossover(1.0, 30),
'mutation': PolynomialMutation(20)
}
def _do(self):
ref_dirs = MultiLayerReferenceDirectionFactory([
UniformReferenceDirectionFactory(n_dim=self.n_dim,
n_partitions=12,
scaling=1),
UniformReferenceDirectionFactory(n_dim=self.n_dim,
n_partitions=12,
scaling=0.7)
]).do()
#UniformReferenceDirectionFactory(n_dim=self.n_dim,n_points=self.n_points, n_partitions=self.n_partitions, scaling=self.scaling).do()
self.n_points = ref_dirs.shape[0]
self.seq = np.tile(self.seq, [ref_dirs.shape[0], 1])
ref_dirs = np.multiply(ref_dirs, self.seq)
sum = np.sum(ref_dirs, axis=1)
sum = np.tile(sum, [ref_dirs.shape[1], 1]).transpose()
ref_dirs = np.divide(ref_dirs, sum)
return ref_dirs
from pymoo.experimental.pbi import ReferenceDirectionSurvivalPBI
from pymoo.optimize import minimize
from pymoo.util.reference_direction import UniformReferenceDirectionFactory, MultiLayerReferenceDirectionFactory
from pymop.factory import get_problem
import matplotlib.pyplot as plt
import numpy as np
problem = get_problem("dtlz3", n_var=None, n_obj=15, k=10)
n_gen = 2000
pop_size = 136
ref_dirs = MultiLayerReferenceDirectionFactory([
UniformReferenceDirectionFactory(15, n_partitions=2, scaling=1.0),
UniformReferenceDirectionFactory(15, n_partitions=1, scaling=0.5)
]).do()
# create the pareto front for the given reference lines
pf = problem.pareto_front(ref_dirs)
ideal_point = []
nadir_point = []
def my_callback(algorithm):
ideal_point.append(np.copy(algorithm.survival.ideal_point))
nadir_point.append(np.copy(algorithm.survival.nadir_point))
res = minimize(problem,