def test_should_the_operator_work_with_a_solution_with_three_binary_variables(
self, random_call):
operator = SinglePoint(1.0)
solution1 = BinarySolution(number_of_variables=3,
number_of_objectives=1)
solution1.variables[0] = [True, False, False, True, True, False]
solution1.variables[1] = [True, False, False, True, False, False]
solution1.variables[2] = [True, False, True, True, True, True]
solution2 = BinarySolution(number_of_variables=3,
number_of_objectives=1)
solution2.variables[0] = [False, True, False, False, True, True]
solution2.variables[1] = [True, True, False, False, True, False]
solution2.variables[2] = [True, True, True, False, False, True]
random_call.return_value = 8
offspring = operator.execute([solution1, solution2])
self.assertEqual([True, False, False, True, True, False],
offspring[0].variables[0])
self.assertEqual([True, False, False, False, True, False],
offspring[0].variables[1])
self.assertEqual([True, True, True, False, False, True],
offspring[0].variables[2])
self.assertEqual([False, True, False, False, True, True],
offspring[1].variables[0])
self.assertEqual([True, True, False, True, False, False],
offspring[1].variables[1])
self.assertEqual([True, False, True, True, True, True],
offspring[1].variables[2])
def test_should_the_solution_remain_unchanged_if_the_probability_is_zero(
self):
operator = SinglePoint(0.0)
solution1 = BinarySolution(number_of_variables=1,
number_of_objectives=1)
solution1.variables[0] = [True, False, False, True, True, False]
solution2 = BinarySolution(number_of_variables=1,
number_of_objectives=1)
solution2.variables[0] = [False, True, False, False, True, False]
offspring = operator.execute([solution1, solution2])
self.assertEqual([True, False, False, True, True, False],
offspring[0].variables[0])
self.assertEqual([False, True, False, False, True, False],
offspring[1].variables[0])
def test_should_the_operator_work_if_the_last_bit_is_selected(
self, random_call):
operator = SinglePoint(1.0)
solution1 = BinarySolution(number_of_variables=1,
number_of_objectives=1)
solution1.variables[0] = [True, False, False, True, True, False]
solution2 = BinarySolution(number_of_variables=1,
number_of_objectives=1)
solution2.variables[0] = [False, True, False, False, True, True]
random_call.return_value = 5
offspring = operator.execute([solution1, solution2])
self.assertEqual([True, False, False, True, True, True],
offspring[0].variables[0])
self.assertEqual([False, True, False, False, True, False],
offspring[1].variables[0])
def main() -> None:
bits = 256
problem = OneMax(bits)
algorithm = GenerationalGeneticAlgorithm[BinarySolution, BinarySolution](
problem,
population_size=100,
max_evaluations=150000,
mutation=BitFlip(1.0 / bits),
crossover=SinglePoint(0.9),
selection=BinaryTournamentSelection())
algorithm.run()
result = algorithm.get_result()
logger.info("Algorithm (binary problem): " + algorithm.get_name())
logger.info("Problem: " + problem.get_name())
logger.info("Solution: " + str(result.variables[0]))
logger.info("Fitness: " + str(result.objectives[0]))
def test_should_constructor_raise_an_exception_if_the_probability_is_lower_than_zero(
self):
with self.assertRaises(Exception):
SinglePoint(-12)
def test_should_constructor_raise_an_exception_if_the_probability_is_greater_than_one(
self):
with self.assertRaises(Exception):
SinglePoint(2)
def test_should_constructor_create_a_valid_operator(self):
operator = SinglePoint(0.5)
self.assertEqual(0.5, operator.probability)
def test_should_constructor_create_a_non_null_object(self):
solution = SinglePoint(1.0)
self.assertIsNotNone(solution)