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)) )
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))
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())
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))
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())
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())
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))
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))
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))
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]))
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]))