MOCell

MOCell is a cellular genetic algorithm: the population is arranged on a toroidal grid, and each individual only interacts with its immediate neighbors, which promotes diversity through structured, localized selection.

from jmetal.algorithm.multiobjective.mocell import MOCell
from jmetal.operator.crossover import SBXCrossover
from jmetal.operator.mutation import PolynomialMutation
from jmetal.problem import ZDT1
from jmetal.util.archive import CrowdingDistanceArchive
from jmetal.util.neighborhood import C9
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")

    max_evaluations = 25000
    algorithm = MOCell(
        problem=problem,
        population_size=100,
        neighborhood=C9(10, 10),
        archive=CrowdingDistanceArchive(100),
        mutation=PolynomialMutation(
            probability=1.0 / problem.number_of_variables(), distribution_index=20
        ),
        crossover=SBXCrossover(probability=1.0, distribution_index=20),
        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}")