def __init__(self,
distance_matrix,
initial_solution_strategy='greedy',
neighbor_selection='first',
neighborhood='2-opt',
seed=None):
TSP.__init__(
self,
distance_matrix,
initial_solution_strategy,
neighbor_selection,
neighborhood,
seed)
def test_initial_solution(self):
tsp = TSP(distance_matrix=self.distance_matrix,
initial_solution_strategy='greedy')
assert_equal(len(tsp.current_solution_), tsp.number_of_cities_)
assert_equal(tsp.current_cost_, 7)
tsp = TSP(distance_matrix=self.distance_matrix,
initial_solution_strategy='random')
assert_equal(len(tsp.current_solution_), tsp.number_of_cities_)
assert_raises(AttributeError,
TSP,
distance_matrix=self.distance_matrix,
initial_solution_strategy='error')
def test_run(self):
tsp = TSP(distance_matrix=self.distance_matrix)
assert_raises(NotImplementedError, tsp.run)
def test__select_neighbor(self):
tsp = TSP(distance_matrix=self.distance_matrix)
assert_raises(NotImplementedError, tsp._select_neighbor)
def test__distance(self):
tsp = TSP(distance_matrix=self.distance_matrix)
assert_equal(tsp._distance(3, 4), 1)
assert_equal(tsp._distance(2, 2), 0)
def test__evaluate_solution(self):
tsp = TSP(distance_matrix=self.distance_matrix)
solution = [1, 3, 4, 2]
assert_equal(tsp._evaluate_solution(solution), 9)
def test__neighbor_swap(self):
tsp = TSP(distance_matrix=self.distance_matrix)
solution = [1, 3, 4, 2]
assert_equal(tsp._neighbor_2_opt(solution, 2, 3), [1, 4, 3, 2])