SMPSO

Common imports for these examples:

from jmetal.operator import Polynomial

from jmetal.util import FrontPlot

SMPSO with standard settings

from jmetal.algorithm import SMPSO
from jmetal.component import CrowdingDistanceArchive
from jmetal.problem import DTLZ1

problem = DTLZ1(number_of_objectives=5)

algorithm = SMPSO(
    problem=problem,
    swarm_size=100,
    max_evaluations=25000,
    mutation=Polynomial(probability=1.0/problem.number_of_variables, distribution_index=20),
    leaders=CrowdingDistanceArchive(100)
)

algorithm.run()
front = algorithm.get_result()

pareto_front = FrontPlot(plot_title='SMPSO-DTLZ1-5', axis_labels=problem.obj_labels)
pareto_front.plot(front, reference_front=problem.reference_front)
pareto_front.to_html(filename='SMPSO-DTLZ1-5')

pareto_front = ScatterPlot(plot_title='SMPSO-DTLZ1-5-norm', axis_labels=problem.obj_labels)
pareto_front.plot(front, reference_front=problem.reference_front, normalize=True)
pareto_front.to_html(filename='SMPSO-DTLZ1-5-norm')

SMPSO/RP with standard settings

from jmetal.algorithm import SMPSORP
from jmetal.component import CrowdingDistanceArchiveWithReferencePoint
from jmetal.problem import ZDT1

def points_to_solutions(points):
    solutions = []
    for i, _ in enumerate(points):
        point = problem.create_solution()
        point.objectives = points[i]
        solutions.append(point)

    return solutions

problem = ZDT1(rf_path='resources/reference_front/ZDT1.pf')

swarm_size = 100
reference_points = [[0.8, 0.2], [0.4, 0.6]]
archives_with_reference_points = []

for point in reference_points:
    archives_with_reference_points.append(
        CrowdingDistanceArchiveWithReferencePoint(swarm_size, point)
    )

algorithm = SMPSORP(
    problem=problem,
    swarm_size=swarm_size,
    max_evaluations=25000,
    mutation=Polynomial(probability=1.0/problem.number_of_variables, distribution_index=20),
    reference_points=reference_points,
    leaders=archives_with_reference_points
)

algorithm.run()
front = algorithm.get_result()

pareto_front = FrontPlot(plot_title='SMPSORP-ZDT1', axis_labels=problem.obj_labels)
pareto_front.plot(front, reference_front=problem.reference_front)
pareto_front.update(points_to_solutions(reference_points), legend='reference points')
pareto_front.to_html(filename='SMPSORP-ZDT1')