OMOPSO

OMOPSO is a particle swarm optimization algorithm for multi-objective problems, using an epsilon-dominance archive and uniform/non-uniform mutation to balance convergence and diversity.

from jmetal.algorithm.multiobjective.omopso import OMOPSO
from jmetal.operator.mutation import NonUniformMutation, UniformMutation
from jmetal.problem import ZDT1
from jmetal.util.archive import CrowdingDistanceArchive
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 = ZDT1()
    problem.reference_front = read_solutions(filename="resources/reference_fronts/ZDT1.pf")

    mutation_probability = 1.0 / problem.number_of_variables()
    max_evaluations = 25000
    swarm_size = 100

    algorithm = OMOPSO(
        problem=problem,
        swarm_size=swarm_size,
        epsilon=0.0075,
        uniform_mutation=UniformMutation(probability=mutation_probability, perturbation=0.5),
        non_uniform_mutation=NonUniformMutation(
            mutation_probability, perturbation=0.5, max_iterations=int(max_evaluations / swarm_size)
        ),
        leaders=CrowdingDistanceArchive(100),
        termination_criterion=StoppingByEvaluations(max_evaluations=max_evaluations),
    )

    algorithm.run()
    front = algorithm.result()

    # Save results to file
    print_function_values_to_file(front, "FUN." + algorithm.label)
    print_variables_to_file(front, "VAR." + algorithm.label)

    print(f"Algorithm: {algorithm.get_name()}")
    print(f"Problem: {problem.name()}")
    print(f"Computing time: {algorithm.total_computing_time}")