from jmetal.algorithm.multiobjective.nsgaii import NSGAII
from jmetal.operator import SBXCrossover, PolynomialMutation
from jmetal.problem import ZDT2
from jmetal.util.comparator import GDominanceComparator
from jmetal.util.solution import print_function_values_to_file, print_variables_to_file, read_solutions
from jmetal.util.termination_criterion import StoppingByEvaluations
if __name__ == '__main__':
problem = ZDT2()
problem.reference_front = read_solutions(
filename='resources/reference_front/ZDT2.pf')
reference_point = [0.2, 0.5]
max_evaluations = 25000
algorithm = NSGAII(
problem=problem,
population_size=100,
offspring_population_size=100,
mutation=PolynomialMutation(probability=1.0 /
problem.number_of_variables,
distribution_index=20),
crossover=SBXCrossover(probability=1.0, distribution_index=20),
dominance_comparator=GDominanceComparator(reference_point),
termination_criterion=StoppingByEvaluations(max=max_evaluations))
algorithm.run()
front = algorithm.get_result()
# Save results to file
print_function_values_to_file(front, 'FUN.' + algorithm.label)
from jmetal.algorithm import NSGAII
from jmetal.component.comparator import RankingAndCrowdingDistanceComparator
from jmetal.operator import NullMutation, SBX, BinaryTournamentSelection, Polynomial
from jmetal.problem import ZDT1, ZDT2
from jmetal.component.quality_indicator import HyperVolume
from jmetal.util.laboratory import Experiment
# Configure experiment
problem_list = [ZDT1(), ZDT2()]
algorithm_list = []
for problem in problem_list:
algorithm_list.append(
('NSGAII_A',
NSGAII(problem=problem,
population_size=100,
max_evaluations=25000,
mutation=NullMutation(),
crossover=SBX(probability=1.0, distribution_index=20),
selection=BinaryTournamentSelection(
comparator=RankingAndCrowdingDistanceComparator()))))
algorithm_list.append(
('NSGAII_B',
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(
mutation=PolynomialMutation(probability=1.0 / problem.number_of_variables,
distribution_index=20),
leaders=CrowdingDistanceArchive(100),
termination_criterion=StoppingByEvaluations(max=max_evaluations)
),
algorithm_tag='SMPSO',
problem_tag=problem_tag,
run=run,
)
)
return jobs
if __name__ == '__main__':
# Configure the experiments
jobs = configure_experiment(problems={'ZDT1': ZDT1(), 'ZDT2': ZDT2(), 'ZDT3': ZDT3()}, n_run=31)
# Run the study
output_directory = 'data'
experiment = Experiment(output_dir=output_directory, jobs=jobs)
experiment.run()
# Generate summary file
generate_summary_from_experiment(
input_dir=output_directory,
reference_fronts='/home/user/jMetalPy/resources/reference_front',
quality_indicators=[GenerationalDistance(), EpsilonIndicator(), HyperVolume([1.0, 1.0])]
)
leaders=CrowdingDistanceArchive(100),
termination_criterion=StoppingByEvaluations(
max=max_evaluations)),
algorithm_tag='SMPSO',
problem_tag=problem_tag,
run=run,
))
return jobs
if __name__ == '__main__':
# Configure the experiments
jobs = configure_experiment(problems={
'ZDT1': ZDT1(),
'ZDT2': ZDT2(),
'ZDT3': ZDT3()
},
n_run=31)
# Run the study
output_directory = 'data'
experiment = Experiment(output_dir=output_directory, jobs=jobs)
experiment.run()
# Generate summary file
generate_summary_from_experiment(
input_dir=output_directory,
reference_fronts='/home/user/jMetalPy/resources/reference_front',
quality_indicators=[
termination_criterion=StoppingByEvaluations(
max_evaluations=max_evaluations),
),
algorithm_tag="SMPSO",
problem_tag=problem_tag,
run=run,
))
return jobs
if __name__ == "__main__":
# Configure the experiments
jobs = configure_experiment(problems={
"ZDT1": ZDT1(),
"ZDT2": ZDT2(),
"ZDT3": ZDT3()
},
n_run=25)
# Run the study
output_directory = "data"
experiment = Experiment(output_dir=output_directory, jobs=jobs)
experiment.run()
# Generate summary file
generate_summary_from_experiment(
input_dir=output_directory,
reference_fronts="resources/reference_front",
quality_indicators=[