diff --git a/README.md b/README.md index a8830faf..ae4391e8 100644 --- a/README.md +++ b/README.md @@ -100,7 +100,7 @@ plot_front.plot(front, label='NSGAII-ZDT1', filename='NSGAII-ZDT1', format='png' Pareto front approximation ## Features -The current release of jMetalPy (v1.5.4) contains the following components: +The current release of jMetalPy (v1.5.5) contains the following components: * Algorithms: local search, genetic algorithm, evolution strategy, simulated annealing, random search, NSGA-II, NSGA-III, SMPSO, OMOPSO, MOEA/D, MOEA/D-DRA, MOEA/D-IEpsilon, GDE3, SPEA2, HYPE, IBEA. Preference articulation-based algorithms (G-NSGA-II, G-GDE3, G-SPEA2, SMPSO/RP); Dynamic versions of NSGA-II, SMPSO, and GDE3. * Parallel computing based on Apache Spark and Dask. @@ -118,6 +118,7 @@ The current release of jMetalPy (v1.5.4) contains the following components: ## Changelog +* [v1.5.5] Minor bug fixes. * [v1.5.4] Refactored quality indicators to accept numpy array as input parameter. * [v1.5.4] Added [CompositeSolution](https://github.com/jMetal/jMetalPy/blob/master/jmetal/core/solution.py#L111) class to support mixed combinatorial problems. [#69](https://github.com/jMetal/jMetalPy/issues/69) diff --git a/examples/multiobjective/moead/moead_dtlz2.py b/examples/multiobjective/moead/moead_dtlz2.py index 7763809f..8770b47b 100644 --- a/examples/multiobjective/moead/moead_dtlz2.py +++ b/examples/multiobjective/moead/moead_dtlz2.py @@ -1,4 +1,5 @@ from jmetal.algorithm.multiobjective.moead import MOEAD +from jmetal.core.quality_indicator import HyperVolume, InvertedGenerationalDistance from jmetal.operator import PolynomialMutation, DifferentialEvolutionCrossover from jmetal.problem import DTLZ2 from jmetal.util.aggregative_function import Tschebycheff @@ -14,7 +15,7 @@ algorithm = MOEAD( problem=problem, population_size=300, - crossover=DifferentialEvolutionCrossover(CR=1.0, F=0.5, K=0.5), + crossover=DifferentialEvolutionCrossover(CR=1.0, F=0.5), mutation=PolynomialMutation(probability=1.0 / problem.number_of_variables, distribution_index=20), aggregative_function=Tschebycheff(dimension=problem.number_of_objectives), neighbor_size=20, @@ -27,6 +28,9 @@ algorithm.run() front = algorithm.get_result() + hypervolume = HyperVolume([1.0, 1.0, 1.0]) + print("Hypervolume: " + str(hypervolume.compute([front[i].objectives for i in range(len(front))]))) + # Save results to file print_function_values_to_file(front, 'FUN.' + algorithm.label) print_variables_to_file(front, 'VAR.'+ algorithm.label) diff --git a/examples/multiobjective/moead/moead_iepsilon_lircmop1.py b/examples/multiobjective/moead/moead_iepsilon_lircmop1.py index 08f036d5..3f517a11 100644 --- a/examples/multiobjective/moead/moead_iepsilon_lircmop1.py +++ b/examples/multiobjective/moead/moead_iepsilon_lircmop1.py @@ -15,7 +15,7 @@ algorithm = MOEADIEpsilon( problem=problem, population_size=300, - crossover=DifferentialEvolutionCrossover(CR=1.0, F=0.5, K=0.5), + crossover=DifferentialEvolutionCrossover(CR=1.0, F=0.5), mutation=PolynomialMutation(probability=1.0 / problem.number_of_variables, distribution_index=20), aggregative_function=Tschebycheff(dimension=problem.number_of_objectives), neighbor_size=20, diff --git a/examples/multiobjective/moead/moead_lz09.py b/examples/multiobjective/moead/moead_lz09.py index a716e4d7..e0bf3c10 100644 --- a/examples/multiobjective/moead/moead_lz09.py +++ b/examples/multiobjective/moead/moead_lz09.py @@ -15,7 +15,7 @@ algorithm = MOEAD( problem=problem, population_size=300, - crossover=DifferentialEvolutionCrossover(CR=1.0, F=0.5, K=0.5), + crossover=DifferentialEvolutionCrossover(CR=1.0, F=0.5), mutation=PolynomialMutation(probability=1.0 / problem.number_of_variables, distribution_index=20), aggregative_function=Tschebycheff(dimension=problem.number_of_objectives), neighbor_size=20, diff --git a/examples/multiobjective/moead/moeaddra_lz09.py b/examples/multiobjective/moead/moeaddra_lz09.py index 93c188ba..ea0aba9d 100644 --- a/examples/multiobjective/moead/moeaddra_lz09.py +++ b/examples/multiobjective/moead/moeaddra_lz09.py @@ -1,20 +1,22 @@ from jmetal.algorithm.multiobjective.moead import MOEAD_DRA from jmetal.operator import PolynomialMutation, DifferentialEvolutionCrossover from jmetal.problem import LZ09_F2 +from jmetal.problem.multiobjective.uf import UF1 from jmetal.util.aggregative_function import Tschebycheff from jmetal.util.solution import read_solutions, print_function_values_to_file, print_variables_to_file from jmetal.util.termination_criterion import StoppingByEvaluations +from jmetal.core.quality_indicator import HyperVolume, InvertedGenerationalDistance if __name__ == '__main__': - problem = LZ09_F2() - problem.reference_front = read_solutions(filename='resources/reference_front/LZ09_F2.pf') + problem = UF1() + problem.reference_front = read_solutions(filename='resources/reference_front/UF1.pf') - max_evaluations = 150000 + max_evaluations = 300000 algorithm = MOEAD_DRA( problem=problem, - population_size=300, - crossover=DifferentialEvolutionCrossover(CR=1.0, F=0.5, K=0.5), + population_size=600, + crossover=DifferentialEvolutionCrossover(CR=1.0, F=0.5), mutation=PolynomialMutation(probability=1.0 / problem.number_of_variables, distribution_index=20), aggregative_function=Tschebycheff(dimension=problem.number_of_objectives), neighbor_size=20, @@ -27,6 +29,9 @@ algorithm.run() front = algorithm.get_result() + hypervolume = HyperVolume([2.0, 2.0]) + print("Hypervolume: " + str(hypervolume.compute([front[i].objectives for i in range(len(front))]))) + # Save results to file print_function_values_to_file(front, 'FUN.' + algorithm.label) print_variables_to_file(front, 'VAR.'+ algorithm.label) @@ -34,3 +39,5 @@ print(f'Algorithm: ${algorithm.get_name()}') print(f'Problem: ${problem.get_name()}') print(f'Computing time: ${algorithm.total_computing_time}') + + diff --git a/jmetal/algorithm/multiobjective/ibea.py b/jmetal/algorithm/multiobjective/ibea.py index bf689cd6..12ca0d30 100644 --- a/jmetal/algorithm/multiobjective/ibea.py +++ b/jmetal/algorithm/multiobjective/ibea.py @@ -72,7 +72,7 @@ def compute_fitness_values(self, population: List[S], kappa: float) -> List[S]: for j in range(len(population)): if j != i: population[i].attributes['fitness'] += -np.exp( - -EpsilonIndicator([population[i]]).compute([population[j]]) / self.kappa) + -EpsilonIndicator([population[i].objectives]).compute([population[j].objectives]) / self.kappa) return population def create_initial_solutions(self) -> List[S]: @@ -92,7 +92,7 @@ def replacement(self, population: List[S], offspring_population: List[S]) -> Lis for i in range(join_population_size): join_population[i].attributes['fitness'] += np.exp( - - EpsilonIndicator([join_population[i]]).compute([join_population[index_worst]]) / self.kappa) + - EpsilonIndicator([join_population[i].objectives]).compute([join_population[index_worst].objectives]) / self.kappa) join_population.pop(index_worst) join_population_size = join_population_size - 1 diff --git a/jmetal/algorithm/singleobjective/evolution_strategy.py b/jmetal/algorithm/singleobjective/evolution_strategy.py index 0233b732..2f52a543 100644 --- a/jmetal/algorithm/singleobjective/evolution_strategy.py +++ b/jmetal/algorithm/singleobjective/evolution_strategy.py @@ -7,6 +7,7 @@ from jmetal.util.evaluator import Evaluator, SequentialEvaluator from jmetal.util.generator import Generator, RandomGenerator from jmetal.util.termination_criterion import TerminationCriterion +from jmetal.util.constraint_handling import overall_constraint_violation_degree S = TypeVar('S') R = TypeVar('R') @@ -78,7 +79,7 @@ def replacement(self, population: List[S], offspring_population: List[S]) -> Lis else: population_pool.extend(offspring_population) - population_pool.sort(key=lambda s: s.objectives[0]) + population_pool.sort(key=lambda s: (overall_constraint_violation_degree(s), s.objectives[0])) new_population = [] for i in range(self.mu): diff --git a/jmetal/core/quality_indicator.py b/jmetal/core/quality_indicator.py index d56d3aa4..809ca247 100644 --- a/jmetal/core/quality_indicator.py +++ b/jmetal/core/quality_indicator.py @@ -47,7 +47,7 @@ def get_short_name(self) -> str: class GenerationalDistance(QualityIndicator): - def __init__(self, reference_front: np.array=None): + def __init__(self, reference_front: np.array = None): """ * Van Veldhuizen, D.A., Lamont, G.B.: Multiobjective Evolutionary Algorithm Research: A History and Analysis. Technical Report TR-98-03, Dept. Elec. Comput. Eng., Air Force. Inst. Technol. (1998) @@ -71,11 +71,11 @@ def get_name(self) -> str: class InvertedGenerationalDistance(QualityIndicator): - def __init__(self, reference_front: np.array): + def __init__(self, reference_front: np.array = None): super(InvertedGenerationalDistance, self).__init__(is_minimization=True) self.reference_front = reference_front - def compute(self, solutions: np.array = None): + def compute(self, solutions: np.array): if self.reference_front is None: raise Exception('Reference front is none') diff --git a/jmetal/core/test/test_solution.py b/jmetal/core/test/test_solution.py index a842647b..2b005bee 100644 --- a/jmetal/core/test/test_solution.py +++ b/jmetal/core/test/test_solution.py @@ -81,7 +81,6 @@ def test_should_copy_work_properly(self) -> None: self.assertEqual(solution.attributes, new_solution.attributes) - class IntegerSolutionTestCase(unittest.TestCase): def test_should_constructor_create_a_non_null_object(self) -> None: @@ -119,6 +118,7 @@ def test_should_copy_work_properly(self) -> None: self.assertIs(solution.upper_bound, solution.upper_bound) self.assertEqual(solution.attributes, new_solution.attributes) + class CompositeSolutionTestCase(unittest.TestCase): def test_should_constructor_create_a_valid_not_none_composite_solution_composed_of_a_double_solution(self): composite_solution = CompositeSolution([FloatSolution([1.0], [2.0], 2)]) @@ -134,7 +134,7 @@ def test_should_constructor_raise_an_exception_if_the_number_of_objectives_is_no def test_should_constructor_create_a_valid_soltion_composed_of_a_float_and_an_integer_solutions(self): number_of_objectives = 3 number_of_constraints = 1 - float_solution: FloatSolution = FloatSolution([1.0], [3.0], number_of_objectives, number_of_constraints) + float_solution: FloatSolution = FloatSolution([1.0], [3.0], number_of_objectives, number_of_constraints) integer_solution: IntegerSolution = IntegerSolution([2], [4], number_of_objectives, number_of_constraints) solution: CompositeSolution = CompositeSolution([float_solution, integer_solution]) @@ -153,7 +153,7 @@ def test_should_constructor_create_a_valid_soltion_composed_of_a_float_and_an_in def test_should_copy_work_properly(self): number_of_objectives = 3 number_of_constraints = 1 - float_solution: FloatSolution = FloatSolution([1.0], [3.0], number_of_objectives, number_of_constraints) + float_solution: FloatSolution = FloatSolution([1.0], [3.0], number_of_objectives, number_of_constraints) integer_solution: IntegerSolution = IntegerSolution([2], [4], number_of_objectives, number_of_constraints) solution: CompositeSolution = CompositeSolution([float_solution, integer_solution]) diff --git a/jmetal/operator/crossover.py b/jmetal/operator/crossover.py index 16603535..2e8bc30b 100644 --- a/jmetal/operator/crossover.py +++ b/jmetal/operator/crossover.py @@ -17,7 +17,6 @@ class NullCrossover(Crossover[Solution, Solution]): - def __init__(self): super(NullCrossover, self).__init__(probability=0.0) @@ -38,7 +37,6 @@ def get_name(self): class PMXCrossover(Crossover[PermutationSolution, PermutationSolution]): - def __init__(self, probability: float): super(PMXCrossover, self).__init__(probability=probability) @@ -97,7 +95,6 @@ def get_name(self): class CXCrossover(Crossover[PermutationSolution, PermutationSolution]): - def __init__(self, probability: float): super(CXCrossover, self).__init__(probability=probability) @@ -148,8 +145,8 @@ def __init__(self, probability: float, distribution_index: float = 20.0): raise Exception("The distribution index is negative: " + str(distribution_index)) def execute(self, parents: List[FloatSolution]) -> List[FloatSolution]: - Check.that(type(parents[0]) is FloatSolution, "Solution type invalid: " + str(type(parents[0]))) - Check.that(type(parents[1]) is FloatSolution, "Solution type invalid") + Check.that(issubclass(type(parents[0]), FloatSolution), "Solution type invalid: " + str(type(parents[0]))) + Check.that(issubclass(type(parents[1]), FloatSolution), "Solution type invalid") Check.that(len(parents) == 2, 'The number of parents is not two: {}'.format(len(parents))) offspring = [copy.deepcopy(parents[0]), copy.deepcopy(parents[1])] @@ -229,8 +226,8 @@ def __init__(self, probability: float, distribution_index: float = 20.0): self.distribution_index = distribution_index def execute(self, parents: List[IntegerSolution]) -> List[IntegerSolution]: - Check.that(type(parents[0]) is IntegerSolution, "Solution type invalid") - Check.that(type(parents[1]) is IntegerSolution, "Solution type invalid") + Check.that(issubclass(type(parents[0]), IntegerSolution), "Solution type invalid") + Check.that(issubclass(type(parents[1]), IntegerSolution), "Solution type invalid") Check.that(len(parents) == 2, 'The number of parents is not two: {}'.format(len(parents))) offspring = [copy.deepcopy(parents[0]), copy.deepcopy(parents[1])] @@ -369,7 +366,7 @@ class DifferentialEvolutionCrossover(Crossover[FloatSolution, FloatSolution]): external to the crossover operator. """ - def __init__(self, CR: float, F: float, K: float): + def __init__(self, CR: float, F: float, K: float = 0.5): super(DifferentialEvolutionCrossover, self).__init__(probability=1.0) self.CR = CR self.F = F diff --git a/jmetal/operator/mutation.py b/jmetal/operator/mutation.py index cfa3abcc..013c0d56 100644 --- a/jmetal/operator/mutation.py +++ b/jmetal/operator/mutation.py @@ -53,7 +53,7 @@ def __init__(self, probability: float, distribution_index: float = 0.20): self.distribution_index = distribution_index def execute(self, solution: FloatSolution) -> FloatSolution: - Check.that(type(solution) is FloatSolution, "Solution type invalid") + Check.that(issubclass(type(solution), FloatSolution), "Solution type invalid") for i in range(solution.number_of_variables): rand = random.random() @@ -98,7 +98,7 @@ def __init__(self, probability: float, distribution_index: float = 0.20): self.distribution_index = distribution_index def execute(self, solution: IntegerSolution) -> IntegerSolution: - Check.that(type(solution) is IntegerSolution, "Solution type invalid") + Check.that(issubclass(type(solution), IntegerSolution), "Solution type invalid") for i in range(solution.number_of_variables): if random.random() <= self.probability: diff --git a/jmetal/operator/test/test_crossover.py b/jmetal/operator/test/test_crossover.py index 1974974a..41c72101 100644 --- a/jmetal/operator/test/test_crossover.py +++ b/jmetal/operator/test/test_crossover.py @@ -1,4 +1,5 @@ import unittest +from typing import List from unittest import mock from jmetal.core.operator import Crossover @@ -294,6 +295,27 @@ def test_should_execute_return_the_parents_if_the_crossover_probability_is_zero( self.assertEqual(solution1.variables, offspring[0].variables) self.assertEqual(solution2.variables, offspring[1].variables) + def test_should_execute_work_with_a_solution_subclass_of_float_solution(self): + class NewFloatSolution(FloatSolution): + def __init__(self, lower_bound: List[float], upper_bound: List[float], number_of_objectives: int, + number_of_constraints: int = 0): + super(NewFloatSolution, self).__init__(lower_bound, upper_bound, number_of_objectives, + number_of_constraints) + + solution1 = NewFloatSolution([1, 2], [2, 4], 2, 2) + solution2 = NewFloatSolution([1, 2], [2, 4], 2, 2) + + solution1.variables = [1.5, 2.7] + solution2.variables = [1.7, 3.6] + + crossover: SBXCrossover = SBXCrossover(0.0, 20.0) + offspring = crossover.execute([solution1, solution2]) + + self.assertEqual(2, len(offspring)) + self.assertEqual(solution1.variables, offspring[0].variables) + self.assertEqual(solution2.variables, offspring[1].variables) + + def test_should_execute_produce_valid_solutions_when_crossing_two_single_variable_solutions(self): pass @@ -308,7 +330,7 @@ def test_should_constructor_raise_an_exception_if_the_parameter_list_is_Empty(se CompositeCrossover([]) def test_should_constructor_create_a_valid_operator_when_adding_a_single_crossover_operator(self): - crossover: Crossover = SBXCrossover(0.9, 20.0) + crossover: Crossover = SBXCrossover(0.9, 20.0) operator = CompositeCrossover([crossover]) self.assertIsNotNone(operator) diff --git a/jmetal/operator/test/test_mutation.py b/jmetal/operator/test/test_mutation.py index cfd07758..87752ee8 100644 --- a/jmetal/operator/test/test_mutation.py +++ b/jmetal/operator/test/test_mutation.py @@ -1,4 +1,5 @@ import unittest +from typing import List from jmetal.core.operator import Mutation from jmetal.core.solution import BinarySolution, FloatSolution, IntegerSolution, CompositeSolution @@ -46,8 +47,21 @@ def test_should_the_solution_change__if_the_probability_is_one(self): operator = PolynomialMutation(1.0) solution = FloatSolution([-5, -5, -5], [5, 5, 5], 2) solution.variables = [1.0, 2.0, 3.0] - FloatSolution.lower_bound = [-5, -5, -5] - FloatSolution.upper_bound = [5, 5, 5] + + mutated_solution = operator.execute(solution) + + self.assertNotEqual([1.0, 2.0, 3.0], mutated_solution.variables) + + def test_should_execute_work_with_a_solution_subclass_of_float_solution(self): + class NewFloatSolution(FloatSolution): + def __init__(self, lower_bound: List[float], upper_bound: List[float], number_of_objectives: int, + number_of_constraints: int = 0): + super(NewFloatSolution, self).__init__(lower_bound, upper_bound, number_of_objectives, + number_of_constraints) + + operator = PolynomialMutation(1.0) + solution = NewFloatSolution([-5, -5, -5], [5, 5, 5], 2) + solution.variables = [1.0, 2.0, 3.0] mutated_solution = operator.execute(solution) diff --git a/jmetal/problem/multiobjective/uf.py b/jmetal/problem/multiobjective/uf.py new file mode 100644 index 00000000..3058b7ca --- /dev/null +++ b/jmetal/problem/multiobjective/uf.py @@ -0,0 +1,64 @@ +from math import pi, sin, sqrt + +from jmetal.core.problem import FloatProblem +from jmetal.core.solution import FloatSolution + +""" +.. module:: UF + :platform: Unix, Windows + :synopsis: Problems of the CEC2009 multi-objective competition + +.. moduleauthor:: Antonio J. Nebro +""" + + +class UF1(FloatProblem): + """ Problem UF1. + + .. note:: Unconstrained problem. The default number of variables is 30. + """ + + def __init__(self, number_of_variables: int = 30): + """ :param number_of_variables: number of decision variables of the problem. + """ + super(UF1, self).__init__() + self.number_of_variables = number_of_variables + self.number_of_objectives = 2 + self.number_of_constraints = 0 + + self.obj_directions = [self.MINIMIZE] * self.number_of_objectives + self.obj_labels = ['$ f_{} $'.format(i) for i in range(self.number_of_objectives)] + + self.lower_bound = self.number_of_variables * [-1.0] + self.upper_bound = self.number_of_variables * [1.0] + self.lower_bound[0] = 0.0 + self.upper_bound[0] = 1.0 + + def evaluate(self, solution: FloatSolution) -> FloatSolution: + sum1 = 0 + sum2 = 0 + count1 = 0 + count2 = 0 + + x = solution.variables + + for i in range(2, self.number_of_variables): + y = x[i-1] - sin(6.0 * pi * x[0] + i * pi/solution.number_of_variables) + y = y*y + + if i % 2 is 0: + sum2 += y + count2 +=1 + else: + sum1 +=y + count1 += 1 + + solution.objectives[0] = x[0] + 2.0 * sum1 /(1.0 * count1) + solution.objectives[1] = 1.0 - sqrt(x[0]) + 2.0 * sum2 / (1.0 * count2) + + + return solution + + def get_name(self): + return 'UF1' + diff --git a/resources/reference_front/UF1.pf b/resources/reference_front/UF1.pf new file mode 100644 index 00000000..d4fd7d90 --- /dev/null +++ b/resources/reference_front/UF1.pf @@ -0,0 +1,1000 @@ + 0.0000000e+000 1.0000000e+000 + 1.0010010e-003 9.6836140e-001 + 2.0020020e-003 9.5525626e-001 + 3.0030030e-003 9.4520034e-001 + 4.0040040e-003 9.3672280e-001 + 5.0050050e-003 9.2925394e-001 + 6.0060060e-003 9.2250157e-001 + 7.0070070e-003 9.1629213e-001 + 8.0080080e-003 9.1051253e-001 + 9.0090090e-003 9.0508420e-001 + 1.0010010e-002 8.9994996e-001 + 1.1011011e-002 8.9506664e-001 + 1.2012012e-002 8.9040068e-001 + 1.3013013e-002 8.8592541e-001 + 1.4014014e-002 8.8161920e-001 + 1.5015015e-002 8.7746423e-001 + 1.6016016e-002 8.7344560e-001 + 1.7017017e-002 8.6955071e-001 + 1.8018018e-002 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100644 --- a/setup.py +++ b/setup.py @@ -25,7 +25,7 @@ setup( name='jmetalpy', - version='1.5.4', + version='1.5.5', description='Python version of the jMetal framework', long_description=README, long_description_content_type='text/markdown',