def ch_move_tail(_solution: List): # usun najdalszy przejazd jaki wystepuje w rozwiazaniu
Raportowanie.used_function('ch_move_tail')
new_solution = deepcopy(_solution)
max_p2p_for_truck = [] # maksymalny przejazd dla kazdej smieciarki
max_p2p_for_truck_value = [] # i jego wartość
for route in _solution:
# print("route: ", route)
if len(route) > 2:
p2p_values = []
for i in range( len(route) - 1):
p2p_values.append(bin_locations[route[i]][route[i + 1]])
# print(p2p_values)
od = route[p2p_values.index(max(p2p_values))]
do = route[p2p_values.index(max(p2p_values)) + 1]
max_p2p_for_truck.append([od, do])
max_p2p_for_truck_value.append(bin_locations[od][do])
elif len(route) == 2:
max_p2p_for_truck.append([route[0], route[1]])
max_p2p_for_truck_value.append(bin_locations[route[0]][route[1]])
index_of_max = max_p2p_for_truck_value.index(max(max_p2p_for_truck_value)) # zwroci index najdluzszego przejazdu
[od, do] = max_p2p_for_truck[index_of_max]
# print("od , do", od, do)
# przenies koniec trasy do najblizszej smieciarki
for i in range(len(new_solution)):
if od in new_solution[i]:
# print("solution[",i,"]",new_solution[i])
bin_start_index = new_solution[i].index(do)
tail = new_solution[i][bin_start_index:]
# head = new_solution[i][bin_start_index:]
# print("tail", tail)
first_point = do
end_point = tail[-1]
# znajdz najblizszy punkt do first_point
distances_from_first_point = bin_locations[do]
distances_from_end_point = bin_locations[end_point]
bins_from_first_point = range(len(bin_locations[do]))
bins_from_end_point = range(len(bin_locations[end_point]))
# slownik klucz - nr kosza wartosc odleglosc od niego
bins_distances_from_first_point = dict(zip(bins_from_first_point, distances_from_first_point))
bins_distances_from_end_point = dict(zip(bins_from_end_point,distances_from_end_point ))
new_bins_distances_from_first_point = {}
new_bins_distances_from_end_point = {}
for bin_nr in bins_distances_from_first_point:
if bin_nr not in new_solution[i]:
new_bins_distances_from_first_point[bin_nr] = bins_distances_from_first_point[bin_nr]
for bin_nr in bins_distances_from_end_point:
if bin_nr not in new_solution[i]:
new_bins_distances_from_end_point[bin_nr] = bins_distances_from_end_point[bin_nr]
del new_bins_distances_from_first_point[0]
del new_bins_distances_from_end_point[0]
# znajdz min odleglosc
min_from_end_point = min(new_bins_distances_from_first_point.items(), key=lambda x: x[1])
min_from_first_point = min(new_bins_distances_from_end_point.items(), key=lambda x: x[1])
if min_from_end_point[1] < min_from_first_point[1]:
closest_bin = min_from_end_point[0]
else:
closest_bin = min_from_first_point[0]
new_solution[i] = new_solution[i][:bin_start_index]
bin_pos = [(index, row.index(closest_bin)) for index, row in enumerate(new_solution) if closest_bin in row][0] # bin_pos ->[ktora smieciarka, ktory kosz z kolei]
new_truck = bin_pos[0]
new_solution[new_truck] += deepcopy(tail)
# sprawdz zabronienia
# if check_ban_t1(random_bin):
if check_ban_t2(new_solution) and check_ban_t3(new_solution):
return new_solution
if aspiration(_solution, new_solution): # jesli aspiracja zadziala
return new_solution
return new_solution
function_name = 'ch_returns_poprawa'
# print(x, " -> ", count_cost(x))
cost_x0 = count_cost(x0)
# print("nowy koszt: ",cost_x0)
# ShowSolutions.show_routes(x0, bin_point_list)
cost_x_opt = count_cost(x_opt)
if cost_x0 < cost_x_opt:
# print("xopt",x_opt, " --> ", cost_x_opt)
# print("x0", x0, " --> ", cost_x0)
x_opt = deepcopy(x0)
Raportowanie.used_function(Raportowanie.klucz_slowny_lista_koszt_od_iteracji, [i, cost_x_opt])
Raportowanie.used_function(function_name, i)
solution_change = True
iterations_without_change = 0
else:
iterations_without_change = iterations_without_change + 1
'''skroc o 1 kadencje'''
for type_T in TABU:
for single_tabu in TABU[type_T]:
if len(single_tabu) == 0 or single_tabu[-1] == 1: # jesli kadencja = 0 to usuń zabronienie
TABU[type_T].remove(single_tabu)
else:
single_tabu[-1] = single_tabu[-1] - 1
'''Dodaj nowe elementy do listy TABU'''