def tour_improve(tour,
lk_max_search_roads,
lk_verbose=False,
lk_depth_limit=None):
""" loop over roads ; convert tour to path
and then start Lin-Kernighan-ish algorithm. """
(best_length, best_cities) = (tour.tour_length(), tour.city_sequence())
loop_roads = set(tour) # loop over a duplicate; tour will be modified.
print "===== starting tour_improve with %i paths to check" % (
2 * len(loop_roads))
i = 0
best_iteration = 0
for road in loop_roads:
for backward in (True, False):
i += 1
tour.revert()
tour.tour2path(road, backward)
print "---- calling %i path_search on %s " % (i, str(tour))
tour2 = path_search(tour, [], [], lk_max_search_roads, lk_verbose,
lk_depth_limit)
print "---- done path_search; found length=%f" % tour2.tour_length(
)
if tour2.tour_length() < best_length:
best_length = tour2.tour_length()
best_cities = tour2.city_sequence()
best_iteration = i
best_tour = Tour(best_cities)
best_tour.plot_paths(i, best_iteration)
print "===== finished tour_improve; best is %s " % str(best_tour)
return best_tour, best_iteration
cmdopt = vars(args)
neighbors = cmdopt.get('neighbors')
dsfile = cmdopt.get('file')
depth = cmdopt.get('depth')
verbose = cmdopt.get('verbose')
cities = []
with open(dsfile) as datasetFile:
dataset = csv.reader(datasetFile, delimiter=',')
for row in dataset:
cities.append(City(row[0], int(row[1]), int(row[2])))
random.shuffle(cities)
Tour.init_roads(cities)
tour = Tour(cities)
answer = 'Y'
while answer in ['Yes', 'yes', 'YES', 'y', 'Y']:
tour.plot_cities()
begin = time.time()
tour, iteration = tour_improve(tour, neighbors, verbose, depth)
end = time.time()
duration = end - begin
print "Iterations took ", duration, " seconds."
tour.plot_paths(2 * len(tour), iteration, True, True)
answer = raw_input("Try to improve this tour ? [Y/N] (default No) : ")
if answer in ['Yes', 'yes', 'YES', 'y', 'Y']:
neighbors_in = raw_input(
"Set a new value for neighbors count (default = actual = " +
str(neighbors) + ') : ')
if neighbors_in:
neighbors = int(neighbors_in)
