def __init__(self):
self.evolution_time = 0
self.best_individuals_cf = []
self.worst_individuals_cf = []
self.mean_cost_function_value = []
self.std_cost_function_value = []
self.best_individual = Individual()
def cross_indvidual_random(ind1: Individual, ind2: Individual) -> Individual:
'''
:param ind1:
:param ind2:
:return: new individual cross of ind1 and ind2
'''
random.seed(datetime.now())
pos = random.randint(0, ind1.street_order.shape[0] - 1)
il_el = random.randint(1, min(ind1.street_order.shape[0] - pos, 10))
part1 = ind1.street_order[pos:pos + il_el].copy()
new = ind2.street_order.copy()
for i in range(0, len(part1)):
j = 0
while j < len(new):
if part1[i] == new[j]:
new = np.delete(new, j)
break
j += 1
new = np.array(new)
part1 = np.array(part1)
child = Individual()
pos2 = random.randint(0, len(new))
tmp = np.concatenate((new[0:pos2], part1, new[pos2:len(new)]), axis=None)
child.street_order = tmp
child.genesis = combine_stats(stat1=ind1.genesis, stat2=ind2.genesis)
child.genesis.cross_indvidual_random_counter += 1
child.max_number_of_cars = ind1.max_number_of_cars
child.number_of_cars = np.count_nonzero(child.street_order == -1)
return child
def cross_indvidual_longest_common(ind1: Individual, ind2: Individual) -> Individual:
'''
:param ind1:
:param ind2:
:return: new individual cross of ind1 and ind2
'''
child = Individual()
child.street_order = create_cross_table(np.copy(ind1.street_order), np.copy(ind2.street_order))
child.genesis = combine_stats(stat1=ind1.genesis, stat2=ind2.genesis)
child.genesis.cross_indvidual_longest_common_counter += 1
child.max_number_of_cars = ind1.max_number_of_cars
child.number_of_cars = np.count_nonzero(child.street_order == -1)
return child
def wrapper(func, *args, **kwargs):
def wrapped():
return func(*args, **kwargs)
return wrapped
x = []
random = []
common = []
reapets_num = 250
for i in range(5, 250):
print(i)
first = Individual()
second = Individual()
first.street_order = np.random.randint(low=-1, high=297, size=i)
first.street_order = np.insert(first.street_order, i - 3, -1)
first.street_order = np.insert(first.street_order, i - 2, -1)
first.street_order = np.insert(first.street_order, i - 1, -1)
second.street_order = np.random.randint(low=-1, high=297, size=i)
second.street_order = np.insert(second.street_order, i - 3, -1)
second.street_order = np.insert(second.street_order, i - 2, -1)
second.street_order = np.insert(second.street_order, i - 1, -1)
wrapped = wrapper(cross_indvidual_random, first, second)
wrappedd = wrapper(cross_indvidual_longest_common, first, second)
x.append(i)
random.append(timeit.timeit(wrapped, number=reapets_num))
common.append(timeit.timeit(wrappedd, number=reapets_num))
from data_structers.inputdata import InputData
from data_structers.evolutional_algorithm import evolution_simulator
import random
from datetime import datetime
import copy
import numpy as np
from import_data.distance_matrix_calculator import matrix_array_calculate
import os
random.seed(datetime.now())
data_set = 'trivial'
gmina = "../data/" + data_set
csv_output = "../Reports/" + 'tsp_' + data_set + ".csv"
order_outpur = "../Reports/" + 'tsp_' + data_set + ".txt"
best_solution = 1000000
matrix_array_calculate(gmina + "_streets.csv", gmina + "_distance_matrix")
inp_data = InputData(gmina)
x = Individual(inp_data)
for i in range(100000):
x.street_order = np.arange(1, 7)
np.random.shuffle(x.street_order)
x.calculate_cost_value(inp_data)
if x.cost_function_value < best_solution:
best_solution = x.cost_function_value
print(best_solution)
return func(*args, **kwargs)
return wrapped
xx = []
y = []
yy = []
yyy = []
yyyy = []
yyyyy = []
yyyyyy = []
reapets_num = 3000
for i in range(5, 1000):
x = Individual()
x.street_order = np.random.randint(low=-1, high=297, size=i)
x.street_order = np.insert(x.street_order, i - 3, -1)
x.street_order = np.insert(x.street_order, i - 2, -1)
x.street_order = np.insert(x.street_order, i - 1, -1)
wrapped = wrapper(change_random_element, x)
wrappedd = wrapper(swap_element_order, x)
wrappeddd = wrapper(add_random_car, x)
wrappedddd = wrapper(shift_car, x)
wrappeddddd = wrapper(add_random_comeback, x)
wrappedddddd = wrapper(delete_random_comeback, x)
random_element_stat = []
xx.append(i)
y.append(timeit.timeit(wrapped, number=reapets_num))
yy.append(timeit.timeit(wrappedd, number=reapets_num))