This commit is contained in:
HelQ 2022-09-07 20:26:13 +02:00
parent a254e6658a
commit 8c5c5c48f0
2 changed files with 165 additions and 8 deletions

123
genetic.py Normal file
View File

@ -0,0 +1,123 @@
import random
class genetic:
def __init__(self, chrome):
self.chrome = chrome
self.key = 10
self.pop_size = 50
self.gen_max = 20
self.length = len(chrome) - 1
self.div = self.length // 2
self.rand = list(range(1, self.length + 1))
def create_genome(self):
genome = "0"
exclusive = random.sample(self.rand, self.length)
genome += "".join(map(str, exclusive))
return genome
def find_fitness(self, genome):
fitness = 0
for i in range(len(genome) - 1):
fitness += self.chrome[int(genome[i])][int(genome[i + 1])]
return fitness
def crossOver(self, gen1, gen2):
gen = []
for i in range(self.div):
gen.append(gen1[i])
for i in range(self.div, self.length+1):
if gen2[i] not in gen:
gen.append(gen2[i])
else:
j = 0
while gen1[j] in gen:
j += 1
gen.append(gen1[j])
return ''.join(gen)
def mutation(self, genome):
genome = list(genome)
while True:
gen1 = random.randint(1, self.length - 1)
gen2 = random.randint(1, self.length - 1)
if gen1 != gen2:
genome[gen1], genome[gen2] = genome[gen2], genome[gen1]
break
return ''.join(genome)
def search(self):
gen = 1
population = []
for i in range(self.pop_size):
ind = individual()
ind.genome = self.create_genome()
ind.fitness = self.find_fitness(ind.genome)
population.append(ind)
print("First population:")
for ind in population:
print(ind.genome, ind.fitness)
while gen <= self.gen_max:
new_population = population
key = random.randint(0, 100)
if key > self.key:
for i in range(self.pop_size):
temp1, temp2 = random.sample(population, 2)
new_ind1 = individual()
new_ind1.genome = self.crossOver(temp1.genome, temp2.genome)
new_ind1.fitness = self.find_fitness(new_ind1.genome)
new_ind2 = individual()
new_ind2.genome = self.crossOver(temp2.genome, temp1.genome)
new_ind2.fitness = self.find_fitness(new_ind2.genome)
new_population.append(new_ind1)
new_population.append(new_ind2)
new_population.sort()
new_population.pop()
new_population.pop()
else:
print('mutation')
for i in range(self.pop_size):
temp1 = random.choice(population)
new_ind = individual()
new_ind.genome = self.mutation(temp1.genome)
new_ind.fitness = self.find_fitness(new_ind.genome)
new_population.append(new_ind)
new_population.sort()
new_population.pop()
print("\n")
print("New Generation # ", gen)
print("Genome Fitness")
for i in range(self.pop_size):
print(new_population[i].genome, new_population[i].fitness)
print("\n")
gen += 1
ans = min(population, key=lambda x: x.fitness)
print("Final order: ", ans.genome, ans.fitness)
return ans.genome
class individual:
def __init__(self):
self.genome = 0
self.fitness = 0
def __lt__(self, other):
return self.fitness < other.fitness
def __gt__(self, other):
return self.fitness > other.fitness
def __le__(self, other):
return self.fitness <= other.fitness
def __ge__(self, other):
return self.fitness >= other.fitness

50
main.py
View File

@ -7,6 +7,7 @@ from rubbish import *
from tree import evaluate_values, trash_selection
from truck import Truck
from surface import *
from genetic import genetic
RESOLUTION = 900
SIZE = 60
@ -52,6 +53,11 @@ for i in range(15):
rubbish_list.append(Rubbish(screen, j * 60, i * 60))
path = []
gen = [(truck.y / 60, truck.x / 60)]
fl = 0
length = []
finalLength = []
order = []
while True:
pygame.time.delay(500)
@ -64,11 +70,40 @@ while True:
i.draw_rubbish()
truck.draw_truck()
# finding order to collect rubbish
if fl == 0:
for item in rubbish_list:
print(item.y / 60, item.x / 60, end='\n')
gen.append((item.y / 60, item.x / 60))
for item1 in range(len(gen)):
for item2 in range(len(gen)):
if item1 < item2:
length.append(len(a_star(surface_list, gen[item2]).tree_search(PriorityQueue(), gen[item1], 'R')))
else:
length.append(0)
finalLength.append(length)
length = []
fl = 1
for i in range(len(finalLength)):
for j in range(len(finalLength)):
if i > j:
finalLength[i][j] = finalLength[j][i]
for i in range(len(finalLength)):
for j in range(len(finalLength)):
print(finalLength[i][j], end=',')
print('')
print(finalLength)
order = genetic(finalLength).search()
order = list(map(int, order))
order.pop(0)
for j in range(len(order)):
order[j] -= 1
# finding a path to rubbish
if rubbish_list and not path:
if order and not path:
start = (truck.y / 60, truck.x / 60)
direction = truck.direction
currentRubbish = rubbish_list[0]
currentRubbish = rubbish_list[order[0]]
endpoint = (currentRubbish.y / 60, currentRubbish.x / 60)
# path = bfs(surface_list, endpoint).tree_search(deque(), start, direction)
path = a_star(surface_list, endpoint).tree_search(PriorityQueue(), start, direction)
@ -82,8 +117,8 @@ while True:
truck.change_direction(action)
# the decision that takes what to do with the garbage
if not path and rubbish_list:
data = rubbish_list[0].data_for_decision_tree()
if not path and order:
data = rubbish_list[order[0]].data_for_decision_tree()
print(f'----------\n'
f'Characteristics of the garbage we met:\n'
f'Weight:{data[0]}\nDensity:{data[1]}\n'
@ -94,12 +129,11 @@ while True:
decision = trash_selection(evaluate_values(data))
if decision == [0]:
print('We refused this rubbish because of bad characteristics')
rubbish_list[0].rubbish_refused()
refused_rubbish_list.append(rubbish_list[0])
rubbish_list[order[0]].rubbish_refused()
refused_rubbish_list.append(rubbish_list[order[0]])
else:
print('We take this rubbish because of good characteristics')
rubbish_list.pop(0)
order.pop(0)
pygame.display.flip()
for event in pygame.event.get():