def test_should_the_operator_work_with_permutation_at_the_beginning(self, random_call):
operator = PMXCrossover(1.0)
solution1 = PermutationSolution(number_of_variables=10, number_of_objectives=1)
solution1.variables = [i for i in range(10)]
solution2 = PermutationSolution(number_of_variables=10, number_of_objectives=1)
solution2.variables = [i for i in range(10, 20)]
random_call.side_effect = (0, 5)
offspring = operator.execute([solution1, solution2])
self.assertEqual([10, 11, 12, 13, 14, 5, 6, 7, 8, 9], offspring[0].variables)
self.assertEqual([0, 1, 2, 3, 4, 15, 16, 17, 18, 19], offspring[1].variables)
def create_solution(self) -> PermutationSolution:
new_solution = PermutationSolution(
number_of_variables=self.number_of_variables,
number_of_objectives=self.number_of_objectives)
new_solution.variables = random.sample(
range(1, self.number_of_variables + 1), self.number_of_variables)
return new_solution
def load_initial_solutions(self, warm_startup_info: Mapping,
problem: Problem) -> None:
self.warm_startup_info = warm_startup_info
if warm_startup_info and 'paths' in self.warm_startup_info.keys(
) and len(self.warm_startup_info['paths']) > 0:
from jmetal.util.generator import InjectorGenerator
one_sol_variables = self.warm_startup_info['paths'][0]
solution = PermutationSolution(
number_of_variables=problem.number_of_variables,
number_of_objectives=problem.number_of_objectives)
solution.variables = one_sol_variables
self._initial_solutions.append(problem.evaluate(solution))
for one_sol_variables in self.warm_startup_info['paths'][1:]:
solution = copy(solution)
solution.variables = one_sol_variables
self._initial_solutions.append(problem.evaluate(solution))
generator = InjectorGenerator(solutions=self._initial_solutions)
else:
from jmetal.util.generator import RandomGenerator
generator = RandomGenerator()
self._solution_generator = generator
