from jmetal.algorithm.multiobjective.random_search import RandomSearch
from jmetal.problem import ZDT1
from jmetal.util.solution import read_solutions, print_function_values_to_file, print_variables_to_file
from jmetal.util.termination_criterion import StoppingByEvaluations
if __name__ == '__main__':
problem = ZDT1()
problem.reference_front = read_solutions(
filename='resources/reference_front/ZDT1.pf')
max_evaluations = 1000
algorithm = RandomSearch(problem=problem,
termination_criterion=StoppingByEvaluations(
max_evaluations=max_evaluations))
algorithm.run()
front = algorithm.get_result()
# Save results to file
print_function_values_to_file(front, 'FUN.' + algorithm.label)
print_variables_to_file(front, 'VAR.' + algorithm.label)
print(f'Algorithm: ${algorithm.get_name()}')
print(f'Problem: ${problem.get_name()}')
print(f'Computing time: ${algorithm.total_computing_time}')
algorithm = NSGAIII(
population_evaluator=MultiprocessEvaluator(Configuration.ProcessNum),
problem=problem,
population_size = Configuration.population,
reference_directions=UniformReferenceDirectionFactory(Configuration.goal_num, n_points= Configuration.population - 1),
# offspring_population_size = Configuration.population,
mutation=PolynomialMutation(probability=1.0 / problem.number_of_variables, distribution_index=20),
crossover=SBXCrossover(probability=1.0, distribution_index=20),
termination_criterion = StoppingByEvaluations(max_evaluations=max_evaluations)
# termination_criterion = StoppingByQualityIndicator(quality_indicator=HyperVolume, expected_value=1,
# degree=0.9)
# selection = BinaryTournamentSelection()
)
elif Configuration.algorithm == 'Random':
algorithm = RandomSearch(
problem=problem,
termination_criterion=StoppingByEvaluations(max_evaluations=max_evaluations)
)
"""==========================调用算法模板进行种群进化========================="""
progress_bar = ProgressBarObserver(max=max_evaluations)
algorithm.observable.register(progress_bar)
algorithm.run()
front = algorithm.get_result()
"""==================================输出结果=============================="""
# Save results to file
print_function_values_to_file(front, os.path.join(target_dir, '/FUN.' + algorithm.label))
print_variables_to_file(front, os.path.join(target_dir, '/VAR.' + algorithm.label))
print(f'Algorithm: ${algorithm.get_name()}')
def configurar_RandomSearch(self):
algorithm = RandomSearch(
problem = self.problema,
termination_criterion=StoppingByEvaluations(max_evaluations=self.evaluaciones))
return algorithm
from jmetal.lab.visualization import Plot, InteractivePlot
from jmetal.problem import ZDT1
from jmetal.util.observer import ProgressBarObserver, VisualizerObserver
from jmetal.util.solutions_utils import read_solutions, print_function_values_to_file, print_variables_to_file
from jmetal.util.termination_criterion import StoppingByEvaluations
if __name__ == '__main__':
problem = ZDT1()
problem.reference_front = read_solutions(
filename='resources/reference_front/ZDT1.pf')
max_evaluations = 1000
algorithm = RandomSearch(
problem=problem,
termination_criterion=StoppingByEvaluations(max=max_evaluations))
progress_bar = ProgressBarObserver(max=max_evaluations)
algorithm.observable.register(observer=progress_bar)
algorithm.observable.register(observer=VisualizerObserver(
reference_front=problem.reference_front))
algorithm.run()
front = algorithm.get_result()
# Plot front
plot_front = Plot(plot_title='Pareto front approximation',
reference_front=problem.reference_front,
axis_labels=problem.obj_labels)
plot_front.plot(front,