crossover=SBX(probability=1.0, distribution_index=20),
selection=BinaryTournamentSelection(
comparator=RankingAndCrowdingDistanceComparator()))
observer = VisualizerObserver(problem)
progress_bar = ProgressBarObserver(step=100, maximum=25000)
algorithm.observable.register(observer=observer)
algorithm.observable.register(observer=progress_bar)
algorithm.run()
front = algorithm.get_result()
# Plot frontier to file
pareto_front = ScatterMatplotlib(
plot_title='NSGAII for ZDT1',
number_of_objectives=problem.number_of_objectives)
pareto_front.plot(front,
reference=problem.get_reference_front(),
output='NSGAII-ZDT1',
show=False)
# Save variables to file
SolutionList.print_function_values_to_file(
front, 'FUN.NSGAII.' + problem.get_name())
SolutionList.print_variables_to_file(front,
'VAR.NSGAII.' + problem.get_name())
print('Algorithm (continuous problem): ' + algorithm.get_name())
print('Problem: ' + problem.get_name())
print('Computing time: ' + str(algorithm.total_computing_time))
progress_bar = ProgressBarObserver(step=10, maximum=250)
#algorithm.observable.register(observer=observer)
algorithm.observable.register(observer=progress_bar)
algorithm.run()
front = algorithm.get_result()
# Plot frontier to file
#pareto_front = ScatterMatplotlib(plot_title='NSGAII for IoT-Min', number_of_objectives=problem.number_of_objectives)
#pareto_front.plot(front, reference=problem.get_reference_front(), output='NSGAII-IoT-Min', show=False)
# Save variables to file
SolutionList.print_function_values_to_file(
front, 'FUN.NSGAII.' + problem.run_id + '.' + problem.get_name())
SolutionList.print_variables_to_file(
front, 'VAR.NSGAII.' + problem.run_id + '.' + problem.get_name())
reference_point = [1, 1, 1, 1]
hv = HyperVolume(reference_point)
value = hv.compute(front)
with open("HV." + problem.run_id + '.' + problem.get_name(),
"w") as text_file:
print(f"{value}", file=text_file)
print('Algorithm (binary problem): ' + algorithm.get_name())
print('Problem: ' + problem.get_name())
print('HyperVolume: %f' % value)
print('Computing time: ' + str(algorithm.total_computing_time))
problem.sf.plog.logError(
'Repeated solutions:' +
str(len(problem.sf.js_engine_helper.tested_solutions)) + '\n')
algorithm = NSGAII(
problem=problem,
population_size=100,
max_evaluations=25000,
mutation=Polynomial(probability=1.0 / problem.number_of_variables, distribution_index=20),
crossover=SBX(probability=1.0, distribution_index=20),
selection=BinaryTournamentSelection(comparator=RankingAndCrowdingDistanceComparator())
)
progress_bar = ProgressBarObserver(step=100, maximum=25000)
visualizer = VisualizerObserver()
algorithm.observable.register(observer=progress_bar)
algorithm.observable.register(observer=visualizer)
algorithm.run()
front = algorithm.get_result()
# Plot frontier to file
pareto_front = FrontPlot(plot_title='NSGAII-ZDT1', axis_labels=problem.obj_labels)
pareto_front.plot(front, reference_front=problem.reference_front)
pareto_front.to_html(filename='NSGAII-ZDT1')
# Save variables to file
SolutionList.print_function_values_to_file(front, 'FUN.NSGAII.ZDT1')
SolutionList.print_variables_to_file(front, 'VAR.NSGAII.ZDT1')
print('Algorithm (continuous problem): ' + algorithm.get_name())
print('Problem: ' + problem.get_name())
print('Computing time: ' + str(algorithm.total_computing_time))