from jmetal.util.observer import PrintObjectivesObserver
from jmetal.util.ranking import FastNonDominatedRanking
from jmetal.util.solutions.comparator import MultiComparator
from jmetal.util.termination_criterion import StoppingByEvaluations
if __name__ == '__main__':
problem = TSP(instance='../../resources/TSP_instances/kroA100.tsp')
print('Cities: ', problem.number_of_variables)
algorithm = GeneticAlgorithm(
problem=problem,
population_size=100,
offspring_population_size=100,
mutation=PermutationSwapMutation(1.0 / problem.number_of_variables),
crossover=PMXCrossover(0.8),
selection=BinaryTournamentSelection(
MultiComparator([
FastNonDominatedRanking.get_comparator(),
CrowdingDistance.get_comparator()
])),
termination_criterion=StoppingByEvaluations(max=2500000))
algorithm.observable.register(observer=PrintObjectivesObserver(1000))
algorithm.run()
result = algorithm.get_result()
print('Algorithm: {}'.format(algorithm.get_name()))
print('Problem: {}'.format(problem.get_name()))
print('Solution: {}'.format(result.variables))
def test_should_constructor_create_a_valid_operator(self):
operator = PMXCrossover(0.5)
self.assertEqual(0.5, operator.probability)
def test_should_constructor_create_a_non_null_object(self):
solution = PMXCrossover(1.0)
self.assertIsNotNone(solution)
def test_should_constructor_raises_an_exception_is_probability_is_higher_than_one(
self) -> None:
with self.assertRaises(Exception):
PMXCrossover(1.01)
def test_should_constructor_raises_an_exception_is_probability_is_negative(
self) -> None:
with self.assertRaises(Exception):
PMXCrossover(-1)
metric.update_available_time(available_time)
test_cases = vsc.get_testcases()
IND_SIZE = len(test_cases)
if (IND_SIZE > 1):
# Run GA to find the best NAPFD in current commit
problem = TCPCI(metric=metric, test_cases=test_cases,
number_of_variables=IND_SIZE)
algorithm = GeneticAlgorithm(
problem=problem,
population_size=300,
offspring_population_size=300,
mutation=PermutationSwapMutation(0.01),
crossover=PMXCrossover(0.9),
selection=BinaryTournamentSelection(),
termination_criterion=StoppingByEvaluations(max=60000)
)
# algorithm.observable.register(observer=PrintObjectivesObserver(1000))
algorithm.run()
result = algorithm.get_result()
print(f"Commit: {t} - Fitness: {result.objectives[0]*-1} - Computing time: {algorithm.total_computing_time}")
else:
print(f"Commit: {t} - Fitness: {1}")
# print('Algorithm: ' + algorithm.get_name())
# print('Problem: ' + problem.get_name())
# print('Solution: ' + str(result.variables[0]))