Python OneMax Examples

Example #1

    def setUp(self) -> None:
        problem1 = OneMax(number_of_bits=512)

        self.emas1 = Emas(
            problem=problem1,
            initial_population_size=1000,
            initial_inidividual_energy=10,
            reproduction_threshold=20,
            energy_exchange_operator=FractionEnergyExchange(0.5),
            death_operator=ThresholdDeath(threshold=5, neighbours_operator=RandomNeighbours()),
            termination_criterion=StoppingByEvaluations(max_evaluations=100000),
            neighbours_operator=RandomNeighbours(),
            reproduction_operator=FractionEnergyReproduction(0.5, BitFlipMutation(0.5), SPXCrossover(0.5))
        )

        problem2 = Sphere(number_of_variables=10)
        self.emas2 = Emas(
            problem=problem2,
            initial_population_size=1000,
            initial_inidividual_energy=10,
            reproduction_threshold=20,
            energy_exchange_operator=FractionEnergyExchange(0.5),
            death_operator=ThresholdDeath(threshold=5, neighbours_operator=RandomNeighbours()),
            termination_criterion=StoppingByEvaluations(max_evaluations=50000),
            neighbours_operator=RandomNeighbours(),
            reproduction_operator=FractionEnergyReproduction(0.5, PolynomialMutation(0.5), SBXCrossover(0.5))
        )

Example #2

from jmetal.algorithm.singleobjective.simulated_annealing import SimulatedAnnealing
from jmetal.operator import BitFlipMutation
from jmetal.problem import OneMax
from jmetal.util.solution import print_function_values_to_file, print_variables_to_file
from jmetal.util.termination_criterion import StoppingByEvaluations

if __name__ == '__main__':
    problem = OneMax(number_of_bits=1024)

    max_evaluations = 20000

    algorithm = SimulatedAnnealing(
        problem=problem,
        mutation=BitFlipMutation(probability=1.0 / problem.number_of_bits),
        termination_criterion=StoppingByEvaluations(max=max_evaluations))

    algorithm.run()
    result = algorithm.get_result()

    # Save results to file
    print_function_values_to_file(
        result, 'FUN.' + algorithm.get_name() + "." + problem.get_name())
    print_variables_to_file(
        result, 'VAR.' + algorithm.get_name() + "." + problem.get_name())

    print('Algorithm: ' + algorithm.get_name())
    print('Problem: ' + problem.get_name())
    print('Solution: ' + result.get_binary_string())
    print('Fitness:  ' + str(result.objectives[0]))
    print('Computing time: ' + str(algorithm.total_computing_time))

Example #3

from jmetal.algorithm.multiobjective.nsgaii import NSGAII
from jmetal.operator import BitFlipMutation, SPXCrossover
from jmetal.problem import OneMax
from jmetal.util.comparator import DominanceComparator
from jmetal.util.observer import PrintObjectivesObserver
from jmetal.util.solutions_utils import print_function_values_to_file, print_variables_to_file
from jmetal.util.termination_criterion import StoppingByEvaluations

if __name__ == '__main__':
    binary_string_length = 512
    problem = OneMax(binary_string_length)

    max_evaluations = 20000

    algorithm = NSGAII(
        problem=problem,
        population_size=100,
        offspring_population_size=1,
        mutation=BitFlipMutation(probability=1.0 / binary_string_length),
        crossover=SPXCrossover(probability=1.0),
        termination_criterion=StoppingByEvaluations(max=max_evaluations),
        dominance_comparator=DominanceComparator()
    )

    algorithm.observable.register(observer=PrintObjectivesObserver(1000))

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

    # Save results to file
    print_function_values_to_file(front, 'FUN.'+ algorithm.get_name()+"-"+problem.get_name())

Example #4

from jmetal.algorithm.singleobjective.local_search import LocalSearch
from jmetal.operator import BitFlipMutation
from jmetal.problem import OneMax
from jmetal.util.observer import PrintObjectivesObserver
from jmetal.util.solution import print_function_values_to_file, print_variables_to_file
from jmetal.util.termination_criterion import StoppingByEvaluations

if __name__ == "__main__":
    problem = OneMax(number_of_bits=512)

    max_evaluations = 10000
    algorithm = LocalSearch(
        problem=problem,
        mutation=BitFlipMutation(probability=1.0 / problem.number_of_bits),
        termination_criterion=StoppingByEvaluations(max_evaluations=max_evaluations),
    )

    algorithm.observable.register(observer=PrintObjectivesObserver(100))

    algorithm.run()
    result = algorithm.get_result()

    # Save results to file
    print_function_values_to_file(result, "FUN." + algorithm.get_name() + "." + problem.get_name())
    print_variables_to_file(result, "VAR." + algorithm.get_name() + "." + problem.get_name())

    print("Algorithm: " + algorithm.get_name())
    print("Problem: " + problem.get_name())
    print("Solution: " + result.get_binary_string())
    print("Fitness:  " + str(result.objectives[0]))
    print("Computing time: " + str(algorithm.total_computing_time))

Example #5

File: nsgaii_single_objective_binary.py Project: jMetal/jMetalPy

from jmetal.algorithm.multiobjective.nsgaii import NSGAII
from jmetal.operator import BitFlipMutation, SPXCrossover
from jmetal.problem import OneMax
from jmetal.util.comparator import DominanceComparator
from jmetal.util.solution import print_function_values_to_file, print_variables_to_file
from jmetal.util.termination_criterion import StoppingByEvaluations

if __name__ == "__main__":
    binary_string_length = 512
    problem = OneMax(binary_string_length)

    max_evaluations = 20000

    algorithm = NSGAII(
        problem=problem,
        population_size=100,
        offspring_population_size=1,
        mutation=BitFlipMutation(probability=1.0 / binary_string_length),
        crossover=SPXCrossover(probability=1.0),
        termination_criterion=StoppingByEvaluations(max_evaluations=max_evaluations),
        dominance_comparator=DominanceComparator(),
    )

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

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

    print("Algorithm (continuous problem): " + algorithm.get_name())

Example #6

File: nsgaii_single_objective_binary.py Project: joergkurtwegner/jMetalPy

from jmetal.algorithm.multiobjective.nsgaii import NSGAII
from jmetal.operator import BitFlipMutation, SPXCrossover
from jmetal.problem import OneMax
from jmetal.util.solutions.comparator import DominanceComparator
from jmetal.util.observer import PrintObjectivesObserver
from jmetal.util.solutions import print_function_values_to_file, print_variables_to_file
from jmetal.util.termination_criterion import StoppingByEvaluations

if __name__ == '__main__':
    binary_string_length = 512
    problem = OneMax(binary_string_length)

    max_evaluations = 20000

    algorithm = NSGAII(
        problem=problem,
        population_size=100,
        offspring_population_size=1,
        mutation=BitFlipMutation(probability=1.0 / binary_string_length),
        crossover=SPXCrossover(probability=1.0),
        termination_criterion=StoppingByEvaluations(max=max_evaluations),
        dominance_comparator=DominanceComparator())

    algorithm.observable.register(observer=PrintObjectivesObserver(1000))

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

    # Save results to file
    print_function_values_to_file(
        front, 'FUN.' + algorithm.get_name() + "-" + problem.get_name())

Example #7

File: evolution_strategy_binary.py Project: abfarr/moo2020

from jmetal.algorithm.singleobjective.evolution_strategy import EvolutionStrategy
from jmetal.operator import BitFlipMutation
from jmetal.problem import OneMax
from jmetal.util.termination_criterion import StoppingByEvaluations

if __name__ == '__main__':
    problem = OneMax(number_of_bits=512)

    algorithm = EvolutionStrategy(
        problem=problem,
        mu=1,
        lambda_=10,
        mutation=BitFlipMutation(probability=1.0 / problem.number_of_bits),
        elitist=True,
        termination_criterion=StoppingByEvaluations(max_evaluations=25000))

    algorithm.run()
    result = algorithm.get_result()

    print('Algorithm: ' + algorithm.get_name())
    print('Problem: ' + problem.get_name())
    print('Solution: ' + str(result.variables[0]))
    print('Fitness:  ' + str(result.objectives[0]))
    print('Computing time: ' + str(algorithm.total_computing_time))

Example #8

File: generational_genetic_algorithm_binary.py Project: jMetal/jMetalPy

from jmetal.algorithm.singleobjective.genetic_algorithm import GeneticAlgorithm
from jmetal.operator import BinaryTournamentSelection, BitFlipMutation, SPXCrossover
from jmetal.problem import OneMax
from jmetal.util.observer import PrintObjectivesObserver
from jmetal.util.termination_criterion import StoppingByEvaluations

if __name__ == "__main__":
    problem = OneMax(number_of_bits=512)

    algorithm = GeneticAlgorithm(
        problem=problem,
        population_size=40,
        offspring_population_size=40,
        mutation=BitFlipMutation(1.0 / problem.number_of_bits),
        crossover=SPXCrossover(1.0),
        selection=BinaryTournamentSelection(),
        termination_criterion=StoppingByEvaluations(max_evaluations=20000),
    )

    algorithm.observable.register(observer=PrintObjectivesObserver(100))

    algorithm.run()
    result = algorithm.get_result()

    print("Algorithm: {}".format(algorithm.get_name()))
    print("Problem: {}".format(problem.get_name()))
    print("Solution: " + result.get_binary_string())
    print("Fitness:  " + str(result.objectives[0]))
    print("Computing time: {}".format(algorithm.total_computing_time))

Example #9

File: generational_genetic_algorithm_binary.py Project: abfarr/moo2020

from jmetal.algorithm.singleobjective.genetic_algorithm import GeneticAlgorithm
from jmetal.operator import BitFlipMutation, SPXCrossover, BinaryTournamentSelection
from jmetal.problem import OneMax
from jmetal.util.termination_criterion import StoppingByEvaluations

if __name__ == '__main__':
    problem = OneMax(number_of_bits=1024)

    algorithm = GeneticAlgorithm(
        problem=problem,
        population_size=100,
        offspring_population_size=100,
        mutation=BitFlipMutation(1.0 / problem.number_of_bits),
        crossover=SPXCrossover(1.0),
        selection=BinaryTournamentSelection(),
        termination_criterion=StoppingByEvaluations(max_evaluations=20000))

    algorithm.run()
    result = algorithm.get_result()

    print('Algorithm: {}'.format(algorithm.get_name()))
    print('Problem: {}'.format(problem.get_name()))
    print('Solution: ' + result.get_binary_string())
    print('Fitness:  ' + str(result.objectives[0]))
    print('Computing time: {}'.format(algorithm.total_computing_time))

Example #10

File: local_search_binary.py Project: pombredanne/jMetalPy

from jmetal.algorithm.singleobjective.local_search import LocalSearch
from jmetal.operator import BitFlipMutation
from jmetal.problem import OneMax
from jmetal.util.observer import PrintObjectivesObserver
from jmetal.util.solution_list import print_function_values_to_file, print_variables_to_file
from jmetal.util.termination_criterion import StoppingByEvaluations

if __name__ == '__main__':
    problem = OneMax(number_of_bits=1024)

    max_evaluations = 10000
    algorithm = LocalSearch(
        problem=problem,
        mutation=BitFlipMutation(probability=1.0 / problem.number_of_bits),
        termination_criterion=StoppingByEvaluations(max=max_evaluations)
    )

    objectives_observer = PrintObjectivesObserver(frequency=100)
    algorithm.observable.register(observer=objectives_observer)

    algorithm.run()
    result = algorithm.get_result()

    # Save results to file
    print_function_values_to_file(result, 'FUN.'+ algorithm.get_name() + "." + problem.get_name())
    print_variables_to_file(result, 'VAR.' + algorithm.get_name() + "." + problem.get_name())

    print('Algorithm: ' + algorithm.get_name())
    print('Problem: ' + problem.get_name())
    print('Solution: ' + result.get_binary_string())
    print('Fitness:  ' + str(result.objectives[0]))

Example #11

from jmetal.algorithm.singleobjective.simulated_annealing import SimulatedAnnealing
from jmetal.operator import BitFlipMutation
from jmetal.problem import OneMax
from jmetal.util.solution import print_function_values_to_file, print_variables_to_file
from jmetal.util.termination_criterion import StoppingByEvaluations

if __name__ == "__main__":
    problem = OneMax(number_of_bits=512)

    max_evaluations = 10000

    algorithm = SimulatedAnnealing(
        problem=problem,
        mutation=BitFlipMutation(probability=1.0 / problem.number_of_bits),
        termination_criterion=StoppingByEvaluations(
            max_evaluations=max_evaluations),
    )

    algorithm.run()
    result = algorithm.get_result()

    # Save results to file
    print_function_values_to_file(
        result, "FUN." + algorithm.get_name() + "." + problem.get_name())
    print_variables_to_file(
        result, "VAR." + algorithm.get_name() + "." + problem.get_name())

    print("Algorithm: " + algorithm.get_name())
    print("Problem: " + problem.get_name())
    print("Solution: " + result.get_binary_string())
    print("Fitness:  " + str(result.objectives[0]))