def test_should_copy_work_properly(self) -> None:
solution = IntegerSolution(2, 3, [0, 5], [1, 2])
solution.variables = [1, 2]
solution.objectives = [0.16, -2.34, 9.25]
solution.attributes["attr"] = "value"
new_solution = copy.copy(solution)
self.assertEqual(solution.number_of_variables, new_solution.number_of_variables)
self.assertEqual(solution.number_of_objectives, new_solution.number_of_objectives)
self.assertEqual(solution.variables, new_solution.variables)
self.assertEqual(solution.objectives, new_solution.objectives)
self.assertEqual(solution.lower_bound, new_solution.lower_bound)
self.assertEqual(solution.upper_bound, new_solution.upper_bound)
self.assertIs(solution.lower_bound, solution.lower_bound)
self.assertIs(solution.upper_bound, solution.upper_bound)
self.assertEqual(solution.attributes, new_solution.attributes)
def test_should_copy_work_properly(self) -> None:
solution = IntegerSolution(2, 3, 2, [0, 5], [1, 2])
solution.variables = [1, 2]
solution.objectives = [0.16, -2.34, 9.25]
solution.attributes["attr"] = "value"
new_solution = copy.copy(solution)
self.assertEqual(solution.number_of_variables, new_solution.number_of_variables)
self.assertEqual(solution.number_of_objectives, new_solution.number_of_objectives)
self.assertEqual(solution.number_of_constraints, new_solution.number_of_constraints)
self.assertEqual(solution.variables, new_solution.variables)
self.assertEqual(solution.objectives, new_solution.objectives)
self.assertEqual(solution.lower_bound, new_solution.lower_bound)
self.assertEqual(solution.upper_bound, new_solution.upper_bound)
self.assertIs(solution.lower_bound, solution.lower_bound)
self.assertIs(solution.upper_bound, solution.upper_bound)
self.assertEqual({}, new_solution.attributes)
startTime = timeit.default_timer()
BestTirf = []
BestInterfaceQuantity = []
solutionsResult = []
frontResult = 0
max_evaluations = MAX_EVALUATION
Net = Network(folderName="Topologia2")
problemOTN = OTNProblem(Net, len(Net.LinkBundles))
# problemOTN = OTNProblemFloat(Net, len(Net.LinkBundles))
stopCriterion = StoppingByEvaluationsCustom(max_evaluations, REFERENCE_POINT) # To topology 1, 200 is enough
reference_point = IntegerSolution([LOWER_BOUND], [UPPER_BOUND], problemOTN.number_of_objectives, )
reference_point.objectives = REFERENCE_POINT # Mandatory for HYPE
mutation_probability = 0.08
swarm_size = POPULATION_SIZE
def configure_experiment(problems: dict, n_run: int):
jobs = []
for run in range(n_run):
for problem_tag, problem in problems.items():
jobs.append(
Job(
algorithm=NSGAII(
problem=problem,
population_size=POPULATION_SIZE,
offspring_population_size=POPULATION_SIZE,