def test_solve(self):
"""Asserts an Optimization Model is correctly solved"""
riders = parse_models(model_dicts=test_riders, cls=Rider)
vehicles = parse_models(model_dicts=test_vehicles, cls=Vehicle)
depots = parse_models(model_dicts=test_depots, cls=Depot)
params = get_params()
estimator = LinearEstimator()
problem_builder = ProblemBuilder(params=params, estimator=estimator)
model_builder = OptimizationModelBuilder(
constraints=[CapacityConstraint()])
problem = problem_builder.build(riders, vehicles, depots)
model = model_builder.build(problem)
solution = model.solve()
self.assertTrue(solution, msg='Model could not be solved.')
self.assertEqual(
len(solution),
len(vehicles),
msg='Number of routes do not match number of vehicles.')
stops_in_solution = [stop for route in solution for stop in route]
for stop_ix in range(len(problem.stops)):
self.assertIn(stop_ix,
stops_in_solution,
msg=f'Stop {stop_ix} not in solution.')
def test_build(self):
"""Assert the Opt. model is built correctly"""
model_builder = OptimizationModelBuilder(
constraints=[CapacityConstraint()])
problem = self.problem
model = model_builder.build(problem)
self.assertTrue(model, msg='Opt. model built incorrectly.')
self.assertEqual(model.manager.GetNumberOfVehicles(),
len(self.vehicles),
msg='Number of vehicles in manager is incorrect.')
self.assertEqual(model.manager.GetNumberOfIndices(),
len(self.vehicles) * 2 + len(self.stops) -
len(problem.depots),
msg='Number of indices in manager is incorrect.')
self.assertTrue(model.solver, msg='Solver could not be instantiated.')
self.assertTrue(model.search_parameters,
msg='Search params could not be built.')
self.assertEqual(model.search_parameters.time_limit,
Duration(seconds=self.params.SEARCH_TIME_LIMIT),
msg='Time limit is incorrect in the search params.')
self.assertEqual(
model.search_parameters.solution_limit,
self.params.SEARCH_SOLUTIONS_LIMIT,
msg='Solutions limit is incorrect in the search params.')
self.assertEqual(
model.search_parameters.first_solution_strategy,
FIRST_SOLUTION_STRATEGY[self.params.FIRST_SOLUTION_STRATEGY],
msg='First solution strategy is incorrect in the search params.')
self.assertEqual(
model.search_parameters.local_search_metaheuristic,
LOCAL_SEARCH_METAHEURISTIC[self.params.SEARCH_METAHEURISTIC],
msg='Search metaheuristic is incorrect in the search params.')
self.assertTrue(model.solver.HasDimension('capacity_constraint'),
msg='Capacity constraint not added.')
def test_set_objective_function(self):
"""Asserts the objective function is added to the solver"""
model_builder = OptimizationModelBuilder(
constraints=[CapacityConstraint()])
problem = self.problem
manager = RoutingIndexManager(
len(problem.stops), # Number of locations
len(problem.vehicles), # Number of vehicles
problem.starts, # Start list of Vehicles
problem.ends # End list of Vehicles
)
solver = RoutingModel(manager)
model_builder._set_objective_function(problem, manager, solver)
self.assertTrue(solver, msg='Objective function set incorrectly.')
def test_apply_constraints_capacity_constraint(self):
"""Asserts constraints are read correctly by the solver"""
model_builder = OptimizationModelBuilder(
constraints=[CapacityConstraint()])
problem = self.problem
manager = RoutingIndexManager(
len(problem.stops), # Number of locations
len(problem.vehicles), # Number of vehicles
problem.starts, # Start list of Vehicles
problem.ends # End list of Vehicles
)
solver = RoutingModel(manager)
model_builder._apply_constraints(problem, manager, solver)
self.assertTrue(solver, msg='Constraints added incorrectly.')
self.assertTrue(solver.HasDimension('capacity_constraint'),
msg='Capacity constraint not added.')
def test_parse_routes(self):
"""Asserts that Routes are correctly parsed from the Opt. solution"""
params = get_params()
estimator = LinearEstimator()
problem_builder = ProblemBuilder(params=params, estimator=estimator)
model_builder = OptimizationModelBuilder(
constraints=[CapacityConstraint()])
riders = parse_models(model_dicts=test_riders, cls=Rider)
vehicles = parse_models(model_dicts=test_vehicles, cls=Vehicle)
depots = parse_models(model_dicts=test_depots, cls=Depot)
problem = problem_builder.build(riders, vehicles, depots)
model = model_builder.build(problem)
solution = model.solve()
routes = Router._parse_routes(problem, solution)
self.assertTrue(routes, msg='Routes could not be built.')
for route in routes:
self.assertTrue(route['vehicle_id'], msg='Route without vehicle.')
self.assertTrue(len(route['stops']) > 1,
msg='Route with single stop.')
def test_route(self):
"""Asserts the main routing method works correctly"""
params = get_params()
estimator = LinearEstimator()
problem_builder = ProblemBuilder(params=params, estimator=estimator)
model_builder = OptimizationModelBuilder(
constraints=[CapacityConstraint()])
router = Router(problem_builder=problem_builder,
optimization_model_builder=model_builder)
riders = parse_models(model_dicts=test_riders, cls=Rider)
vehicles = parse_models(model_dicts=test_vehicles, cls=Vehicle)
depots = parse_models(model_dicts=test_depots, cls=Depot)
routes = router.route(riders, vehicles, depots)
self.assertTrue(routes, msg='Routes could not be built.')
for route in routes:
self.assertTrue(route['vehicle_id'], msg='Route without vehicle.')
self.assertTrue(len(route['stops']) > 1,
msg='Route with single stop.')
def test_build_search_parameters(self):
"""Asserts the heuristic search parameters are correctly created"""
search_parameters = OptimizationModelBuilder._build_search_parameters(
self.problem)
self.assertTrue(search_parameters,
msg='Search params could not be built.')
self.assertEqual(search_parameters.time_limit,
Duration(seconds=self.params.SEARCH_TIME_LIMIT),
msg='Time limit is incorrect in the search params.')
self.assertEqual(
search_parameters.solution_limit,
self.params.SEARCH_SOLUTIONS_LIMIT,
msg='Solutions limit is incorrect in the search params.')
self.assertEqual(
search_parameters.first_solution_strategy,
FIRST_SOLUTION_STRATEGY[self.params.FIRST_SOLUTION_STRATEGY],
msg='First solution strategy is incorrect in the search params.')
self.assertEqual(
search_parameters.local_search_metaheuristic,
LOCAL_SEARCH_METAHEURISTIC[self.params.SEARCH_METAHEURISTIC],
msg='Search metaheuristic is incorrect in the search params.')
from utils.logging_utils import configure_logs
"""Main method to execute the Router"""
# CLI parsing
parser = argparse.ArgumentParser(description='Route some school buses.')
parser.add_argument('--input-dir',
type=str,
help='Directory for reading the Input. Default is ./input',
default='./input')
parser.add_argument(
'--output-dir',
type=str,
help='Directory for reading the Output. Default is ./output',
default='./output',
)
args = parser.parse_args()
input_dir = args.input_dir
output_dir = args.output_dir
# Method execution
configure_logs()
riders, vehicles, depots, params = read_entities(input_dir)
estimator = LinearEstimator()
problem_builder = ProblemBuilder(params=params, estimator=estimator)
optimization_model_builder = OptimizationModelBuilder(
constraints=[CapacityConstraint()])
router = Router(problem_builder=problem_builder,
optimization_model_builder=optimization_model_builder)
routes = router.route(riders, vehicles, depots)
write_routes(output_dir, routes)