def __init__(self,
objective_function,
num_objectives,
num_variables,
k,
**kwargs):
assert num_objectives > 1
assert k >= 1 and k < num_variables
assert k % (num_objectives - 1) == 0
self.max_objectives = None
self.min_objectives = None
if num_objectives == 3:
self.max_objectives = [10.0, 10.0, 10.0]
self.min_objectives = [0.0, 0.0, 0.0]
elif num_objectives == 5:
self.max_objectives = [10.0, 10.0, 10.0, 10.0, 12.0]
self.min_objectives = [0.0, 0.0, 0.0, 0.0, 0.0]
self.min_bounds = [0.0] * num_variables
self.max_bounds = [2.0 * i for i in range(1, num_variables + 1)]
MultiObjectiveTestProblem.__init__(self,
objective_function,
num_objectives,
**kwargs)
self.k = k
self.num_variables = num_variables
self.is_deterministic = True
self.do_maximize = False
if num_objectives <= 4:
self.default_reference_set_size = 500
else:
self.default_reference_set_size = 1000
def __init__(self, objective_function, num_objectives, num_variables, phenome_preprocessor=None, **kwargs):
assert num_variables > num_objectives
self.num_variables = num_variables
self.min_bounds = [0.0] * num_variables
self.max_bounds = [1.0] * num_variables
bounds = (self.min_bounds, self.max_bounds)
preprocessor = BoundConstraintsChecker(bounds, phenome_preprocessor)
self.is_deterministic = True
self.do_maximize = False
MultiObjectiveTestProblem.__init__(self,
objective_function,
num_objectives,
phenome_preprocessor=preprocessor,
**kwargs)
