111 lines
3.8 KiB
Python
111 lines
3.8 KiB
Python
import random
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### prawdopodobieństwo mutacji
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mutation_prob = 0.02
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### ilość osobników w pokoleniu
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generation_size = 4
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### liczba pokoleń
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number_of_generations = 4
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### liczba paczek
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number_of_packages = 10
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### liczba regałów
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number_of_racks = 5
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### jak bardzo promowane są osobniki wykorzystujące całą pojemność regału
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amount_of_promotion = 3
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def first_gen():
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first_generation = []
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for individual in range(generation_size):
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individual = []
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for pack in range(number_of_packages):
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r = random.randint(0,number_of_racks-1)
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individual.append(r)
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first_generation.append(individual)
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return first_generation
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def evaluation(individual):
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# im większy fitness tym lepszy osobnik
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# print("regały: ",racks)
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rest_of_capacity = racks.copy()
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# print("początkowa pojemność: ",rest_of_capacity)
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for i in range(number_of_packages):
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rest_of_capacity[individual[i]] -= packages[i]
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# print("pozostała pojemność: ",rest_of_capacity)
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fitness = 0
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for i in range(number_of_racks):
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# jak regał jest przepełniony, zmniejsza fitness osobnika
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if rest_of_capacity[i] < 0:
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fitness += rest_of_capacity[i]
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# delikane promowanie osobników wykorzystujących regały w pełni
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elif rest_of_capacity[i] == 0:
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fitness += amount_of_promotion
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### tu dodaj to co zrobi Andrzej
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return fitness
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def roulette(generation):
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# print('pokolenie: ', generation)
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evaluations = []
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for i in range(generation_size):
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individual_fitness = evaluation(generation[i])
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evaluations.append(individual_fitness)
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# print("tablica niedopasowań: ", evaluations)
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minimum = min(evaluations)
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# dodaję tą 1 żeby nie wywalać najgorszego osobnika
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normalized = [x+(-1*minimum)+1 for x in evaluations]
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# print(normalized)
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sum_of_normalized = sum(normalized)
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roulette_tab = [x/sum_of_normalized for x in normalized]
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# print(roulette_tab)
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for i in range(1,generation_size-1):
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roulette_tab[i] += roulette_tab[i-1]
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# wpisuję 1 ręcznie, bo czasem liczby nie sumowały się idealnie do 1
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#(niedokładność komputera)
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roulette_tab[generation_size-1] = 1
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# print("ruletka: ", roulette_tab)
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survivors = []
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for individual in range(generation_size):
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random_number = random.random()
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interval_number = 0
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while random_number > roulette_tab[interval_number]:
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interval_number += 1
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survivors.append(generation[interval_number])
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# print('przetrwali: ',survivors)
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return survivors
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def crossover(individual1, individual2):
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cut = random.randint(1,number_of_packages-1)
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new1 = individual1[:cut]
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new2 = individual2[:cut]
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new1 = new1 + individual2[cut:]
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new2 = new2 + individual1[cut:]
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# print(individual1)
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# print(individual2)
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# print(new1)
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# print(new2)
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# print(cut)
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return new1, new2
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def mutation(individual):
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print(individual)
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locus = random.randint(0,number_of_packages-1)
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individual[locus] = random.randint(0,number_of_racks-1)
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return individual
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### lista paczek, indeks to id paczki, wartość w liście to jej waga
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packages = [random.randint(2,10) for i in range(number_of_packages)]
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### lista regałów, indeks to id regału, wartość w liście to jego pojemność
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racks = [random.randint(10,20) for i in range(number_of_racks)]
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# print(packages)
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# print(racks)
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first_generation = first_gen()
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# crossover(first_generation[0],first_generation[1])
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# descendants = []
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# for i in range(0,generation_size,2):
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# pair = crossover(first_generation[i],first_generation[i+1])
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# for each in pair:
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# descendants.append(each)
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# print(descendants)
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print("first gen: ",first_generation)
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roulette(first_generation)
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