def main() -> None:
problem = Kursawe()
algorithm = SMPSO(problem=problem,
swarm_size=100,
max_evaluations=25000,
mutation=Polynomial(1.0 / problem.number_of_variables,
distribution_index=20),
leaders=CrowdingDistanceArchive(100))
algorithm.run()
result = algorithm.get_result()
SolutionListOutput[FloatSolution].print_function_values_to_file(
"FUN." + problem.get_name(), result)
logger.info("Algorithm (continuous problem): " + algorithm.get_name())
logger.info("Problem: " + problem.get_name())
def test_should_SMPSO_work_when_solving_problem_ZDT1_with_standard_settings(self):
problem = ZDT1()
algorithm = SMPSO(
problem=problem,
swarm_size=100,
mutation=PolynomialMutation(probability=1.0 / problem.number_of_variables, distribution_index=20),
leaders=CrowdingDistanceArchive(100),
termination_criterion=StoppingByEvaluations(max_evaluations=25000),
)
algorithm.run()
front = algorithm.get_result()
hv = HyperVolume(reference_point=[1, 1])
value = hv.compute([front[i].objectives for i in range(len(front))])
self.assertTrue(value >= 0.655)
if __name__ == '__main__':
problem = DTLZ1(number_of_objectives=5)
max_evaluations = 25000
algorithm = SMPSO(
problem=problem,
swarm_size=100,
mutation=PolynomialMutation(probability=1.0 / problem.number_of_variables, distribution_index=20),
leaders=CrowdingDistanceArchive(100),
termination_criterion=StoppingByEvaluations(max=max_evaluations)
)
algorithm.observable.register(observer=ProgressBarObserver(max=max_evaluations))
algorithm.run()
front = algorithm.get_result()
label = algorithm.get_name() + "." + problem.get_name()
# 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())
# Save results to file
print_function_values_to_file(front, 'FUN.' + algorithm.label)