def test_should_constructor_create_a_valid_problem_with_default_settings(self) -> None:
problem = ZDT6()
self.assertEqual(10, problem.number_of_variables)
self.assertEqual(2, problem.number_of_objectives)
self.assertEqual(0, problem.number_of_constraints)
self.assertEqual(10 * [0.0], problem.lower_bound)
self.assertEqual(10 * [1.0], problem.upper_bound)
def test_should_create_solution_create_a_valid_float_solution(self) -> None:
problem = ZDT6()
solution = problem.create_solution()
self.assertEqual(10, solution.number_of_variables)
self.assertEqual(10, len(solution.variables))
self.assertEqual(2, solution.number_of_objectives)
self.assertEqual(2, len(solution.objectives))
self.assertEqual(0, problem.number_of_constraints)
self.assertEqual(10 * [0.0], problem.lower_bound)
self.assertEqual(10 * [1.0], problem.upper_bound)
self.assertTrue(all(value >= 0.0 for value in solution.variables))
self.assertTrue(all(value <= 1.0 for value in solution.variables))
def test_should_get_name_return_the_right_name(self):
problem = ZDT6()
self.assertEqual("ZDT6", problem.get_name())
def test_should_constructor_create_a_non_null_object(self) -> None:
problem = ZDT6()
self.assertIsNotNone(problem)
# Solving SCH Problem using NSGAII
from jmetal.algorithm.multiobjective.nsgaii import NSGAII
from jmetal.operator import SBXCrossover, PolynomialMutation
from jmetal.util.termination_criterion import StoppingByEvaluations
from jmetal.util.observer import ProgressBarObserver, VisualizerObserver
from jmetal.lab.visualization import Plot, InteractivePlot
from jmetal.problem.multiobjective.zdt import ZDT6
if __name__ == '__main__':
problem = ZDT6()
max_evaluations = 20000
algorithm = NSGAII(
problem = problem,
population_size = 100,
offspring_population_size = 100,
mutation=PolynomialMutation(probability=0.05, distribution_index=20),
crossover=SBXCrossover(probability=1.0, distribution_index=20),
termination_criterion=StoppingByEvaluations(max=max_evaluations)
)
algorithm.observable.register(observer=ProgressBarObserver(max=max_evaluations))
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, label=algorithm.label, filename=algorithm.get_name())
# Plot interactive front
plot_front = InteractivePlot(plot_title='Pareto front approximation', reference_front=problem.reference_front, axis_labels=problem.obj_labels)
plot_front.plot(front, label=algorithm.label, filename=algorithm.get_name())