stopping_criteria_tsp.py

# Everything put together
best_solution = [-1,np.inf,np.array([])]
for i in range(100000):
    if i%100==0: print(i, fitnes_list.min(), fitnes_list.mean(), datetime.now().strftime("%d/%m/%y %H:%M"))
    fitnes_list = get_all_fitnes(mutated_pop,cities_dict)
    
    #Saving the best solution
    if fitnes_list.min() < best_solution[1]:
        best_solution[0] = i
        best_solution[1] = fitnes_list.min()
        best_solution[2] = np.array(mutated_pop)[fitnes_list.min() == fitnes_list]
    
    progenitor_list = progenitor_selection(population_set,fitnes_list)
    new_population_set = mate_population(progenitor_list)
    
    mutated_pop = mutate_population(new_population_set)