def __init__(
self,
problem: MOProblem,
pop_size: int,
pop_params: Dict = None,
use_surrogates: bool = False,
):
super().__init__(problem, pop_size)
self.lower_limits = self.problem.get_variable_lower_bounds()
self.upper_limits = self.problem.get_variable_upper_bounds()
self.individuals_archive = {}
self.objectives_archive = {}
self.uncertainty_archive = {}
self.gen_count = 1
#self.individuals_archive[str(self.gen_count)] = self.individuals
#self.objectives_archive[str(self.gen_count)] = self.objectives
#self.uncertainty_archive[str(self.gen_count)] = self.uncertainity
if pop_params is None:
design = "LHSDesign"
if pop_params is not None:
if "design" in pop_params.keys():
design = pop_params["design"]
else:
design = "LHSDesign"
if design == "InitSamples":
individuals = pop_params["init_pop"]
else:
individuals = create_new_individuals(design, problem, pop_size)
self.add(individuals, use_surrogates)
self.xover = SBX_xover()
self.mutation = BP_mutation(self.lower_limits, self.upper_limits)
def __init__(self, problem: MOProblem, pop_size: int, pop_params: Dict = None):
super().__init__(problem, pop_size)
self.lower_limits = self.problem.get_variable_lower_bounds()
self.upper_limits = self.problem.get_variable_upper_bounds()
if pop_params is None:
design = "LHSDesign"
if pop_params is not None:
if "design" in pop_params.keys():
design = pop_params["design"]
else:
design = "LHSDesign"
individuals = create_new_individuals(design, problem, pop_size)
self.add(individuals)
self.xover = SBX_xover()
self.mutation = BP_mutation(self.lower_limits, self.upper_limits)