def large():
city_map = Map.from_atsp('atsp/tests/test_data/rbg403.atsp')
solver = SimulatedAnnealing(city_map, cooling_factor=0.999)
for _ in range(10):
solver.solve(timeout=121, print_timeout=5)
print(solver.log.time_summary())
print(solver.log.best_summary())
def small():
city_map = Map.from_atsp('atsp/tests/test_data/ftv47.atsp')
solver = SimulatedAnnealing(city_map, cooling_factor=0.99997)
for _ in range(10):
solver.solve(timeout=31, print_timeout=5)
print(solver.log.time_summary())
print(solver.log.best_summary())
def medium():
city_map = Map.from_atsp('../atsp/tests/test_data/ftv170.atsp')
solver = new_solver(city_map)
for _ in range(10):
solver.solve(timeout=63, print_timeout=5)
print(solver.log.time_summary())
print(solver.log.best_summary())
def large():
city_map = Map.from_atsp('../atsp/tests/test_data/rbg403.atsp')
solver = new_solver(city_map)
for _ in range(10):
solver.solve(timeout=125, print_timeout=5)
print(solver.log.time_summary())
print(solver.log.best_summary())
def measure_brute_force(self):
values = []
for _ in range(self.repetitions):
city_map = Map.from_random_matrix(size=self.size)
atsp = Atsp(city_map)
start = time.time()
atsp.brute_force()
time_taken = time.time() - start
values.append(time_taken)
# logger.debug(time_taken)
return sum(values) / len(values)
def __init__(self,
file_path,
known_best_value,
population_size,
repetitions=10,
timeout=30):
city_map = Map.from_atsp(file_path)
self.known_best_value = known_best_value
self.solver = GeneticSolver(city_map,
population_size=population_size,
crossover_coefficient=0.8,
mutation_coefficient=0.1)
self.repetitions = repetitions
self.timeout = timeout
def _measure(self, action):
values = []
timeouts = 0
for _ in range(self.repetitions):
city_map = Map.from_random_matrix(size=self.size)
start = time.time()
try:
action(city_map, self.timeout)
time_taken = time.time() - start
except TimeoutError:
time_taken = self.timeout
timeouts += 1
values.append(time_taken)
# logger.debug(time_taken)
return sum(values) / len(values), timeouts
def city_map(test_set):
test_set_path = os.path.join(os.path.dirname(__file__), 'test_data',
'{}.txt'.format(test_set))
return Map.from_file(test_set_path)
def load(file_path):
city_map = Map.from_file(file_path) if file_path.endswith(
'txt') else Map.from_atsp(file_path)
menu = MainMenu(city_map)
menu.display()
def __init__(self, file_path, known_best_value, cooling_factor, repetitions=10, timeout=30):
city_map = Map.from_atsp(file_path)
self.known_best_value = known_best_value
self.solver = SimulatedAnnealing(city_map, cooling_factor=cooling_factor)
self.repetitions = repetitions
self.timeout = timeout