kompletny algorytm genetyczny bez rozwozenia boxow i interface

This commit is contained in:
tomasz 2020-05-18 12:53:51 +02:00
parent d25c4213de
commit ac04e30a96
13 changed files with 324 additions and 163 deletions

View File

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@ -8,7 +8,11 @@ class Data:
self.mapa = [] self.mapa = []
self.unbox = [] self.unbox = []
self.astarMap = [] self.astarMap = []
self.geny = []
self.kordyWozka = None
self.jakLiczycKoszt = None
self.best = None
self.histZmian = []
def genMap(self, mapa): def genMap(self, mapa):
tmpMap =[] tmpMap =[]

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@ -1,8 +1,8 @@
class Gene: class Gene:
def __init__(self, poczatkowa, koncowa, name): def __init__(self, kordydnaty):
self.poczatkowa = poczatkowa self.kordy = kordydnaty
self.koncowa = koncowa self.unbox1 = None
self.koszt = 0 self.unbox2 = None
self.name = name self.ktoryUnbox = None

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@ -3,6 +3,20 @@ from genetyczny.Gene import Gene
from Mapa.box import Box from Mapa.box import Box
from AStar import AStar from AStar import AStar
import random import random
import numpy
def generateGeny(data):
zajeteRegaly = data.zajeteRegaly[:]
for r in zajeteRegaly:
g = Gene(r)
g.unbox1 = policzCost(data.astarMap,r,data.unbox[0])
if(len(data.unbox) > 1):
g.unbox2 = policzCost(data.astarMap,r,data.unbox[1])
data.geny.append(g)
def znajdzUnbox(data,mapa): def znajdzUnbox(data,mapa):
@ -15,8 +29,7 @@ def znajdzUnbox(data,mapa):
iterator += 1 iterator += 1
data.unbox = unboxy data.unbox = unboxy
def wybierzUnbox(data):
return random.choice(data.unbox)
def policzCost(mapaBoxy, poczatek, koniec): def policzCost(mapaBoxy, poczatek, koniec):
@ -24,31 +37,69 @@ def policzCost(mapaBoxy, poczatek, koniec):
koszt = astar.search(poczatek, koniec, mapaBoxy, 1, 0) koszt = astar.search(poczatek, koniec, mapaBoxy, 1, 0)
return koszt return koszt
def generateChromosome(data, mapaBoxy, wheelxy): def genRandomChromosome(data):
chromosome = [] chromosome = data.geny[:]
regaly = data.zajeteRegaly random.shuffle(chromosome)
random.shuffle(regaly) krotkaKosztJakiUnbox = None
unboxLastGen = None
for r in regaly:
gen0 = Gene(wheelxy,r,"poczatek-regal")
gen0.koszt = policzCost(mapaBoxy, wheelxy, r)
chromosome.append(gen0)
unbox = wybierzUnbox(data)
gen1 = Gene(r,unbox,"regal-unbox")
gen1.koszt = policzCost(mapaBoxy, r, unbox)
chromosome.append(gen1)
for gen in chromosome:
gen.ktoryUnbox = unboxLastGen
krotkaKosztJakiUnbox = wybierzUnbox(gen, data.jakLiczycKoszt)
unboxLastGen = krotkaKosztJakiUnbox[1]
return chromosome return chromosome
def generatePopulation(data, mapaBoxy, wheelxy, ileWPopulacji): def genRandomPopulation(data, ileWPopulacji):
populacja = [] populacja = []
for i in range(ileWPopulacji): for i in range(ileWPopulacji):
populacja.append(generateChromosome(data, mapaBoxy, wheelxy)) populacja.append(genRandomChromosome(data))
return populacja return populacja
def fitness(chromosome, data):
koszt = 0
unboxPoprzedniegoGenu = None
for item, gen in enumerate(chromosome):
if(item == 0):
koszt += policzCost(data.astarMap, data.kordyWozka, gen.kordy)
krotkaKosztJakiUnbox = wybierzUnbox(gen, data.jakLiczycKoszt)
koszt += krotkaKosztJakiUnbox[0]
unboxPoprzedniegoGenu = krotkaKosztJakiUnbox[1]
else:
if unboxPoprzedniegoGenu == 0:
koszt += gen.unbox1
elif unboxPoprzedniegoGenu == 1:
koszt += gen.unbox2
krotkaKosztJakiUnbox = wybierzUnbox(gen, data.jakLiczycKoszt)
koszt += krotkaKosztJakiUnbox[0]
unboxPoprzedniegoGenu = krotkaKosztJakiUnbox[1]
return koszt
def wybierzUnbox(gen, jakLiczycKoszt):
if(jakLiczycKoszt == 0):
x = random.choice([gen.unbox1, gen.unbox2])
if(x == gen.unbox1):
y = 0
else:
y= 1
return (x,y)
elif(jakLiczycKoszt == 1):
return (gen.unbox1,0)
elif(jakLiczycKoszt == 2):
return (gen.unbox2,1)
elif(jakLiczycKoszt == 3):
x = min(gen.unbox1,gen.unbox2)
if(x == gen.unbox1):
y = 0
else:
y = 1
return (x,y)
def randomBox(mapa, regals, ile): def randomBox(mapa, regals, ile):
regals = regals regals = regals
@ -84,3 +135,83 @@ def znajdzBox(mapa, regals):
if(tmp == True): if(tmp == True):
zajeteRegaly.append((x,y)) zajeteRegaly.append((x,y))
return zajeteRegaly return zajeteRegaly
def dwieNajlepsze(populacja, data):
tmpPopulacja = populacja[:]
chromFitness = []
for chrom in populacja:
chromFitness.append(fitness(chrom,data))
bestValue = min(chromFitness)
bestChromIndex = chromFitness.index(bestValue)
pierwsza = tmpPopulacja[bestChromIndex]
if (data.best == None):
data.best = (pierwsza[:],bestValue)
elif(data.best[1] > bestValue):
data.best = (pierwsza[:],bestValue)
tmpPopulacja.pop(bestChromIndex)
chromFitness.pop(bestChromIndex)
bestValue = min(chromFitness)
bestChromIndex = chromFitness.index(bestValue)
druga = tmpPopulacja[bestChromIndex]
tmpPopulacja.pop(bestChromIndex)
chromFitness.pop(bestChromIndex)
return (pierwsza, druga)
def genPopulacje(pierwszy, drugi, ileWPopulacji, fragmentLiczba, wspMutacji):
ileWChrom = len(pierwszy)
fragment = round(fragmentLiczba*ileWChrom)
nowaPopulacja = []
for i in range(ileWPopulacji):
nowaPopulacja.append(crossover(pierwszy,drugi,fragment, wspMutacji))
return nowaPopulacja
def crossover(pierwszy, drugi, fragmentLiczba, wspMutacji):
ileWChrom = len(pierwszy)
tmp = random.randint(0, ileWChrom-fragmentLiczba)
kordyFragment = (tmp,tmp+fragmentLiczba)
nowyChrom = [None] * ileWChrom
iterator = kordyFragment[1]
pomIterator = kordyFragment[1]
nowyChrom[kordyFragment[0]:kordyFragment[1]] = pierwszy[kordyFragment[0]:kordyFragment[1]]
while(None in nowyChrom):
if(iterator > ileWChrom - 1):
iterator = 0
if(pomIterator > ileWChrom - 1):
pomIterator = 0
if(nowyChrom[iterator] == None and drugi[pomIterator] not in nowyChrom):
nowyChrom[iterator] = drugi[pomIterator]
iterator += 1
pomIterator += 1
elif(nowyChrom[iterator] == None and drugi[pomIterator] in nowyChrom):
pomIterator +=1
nowyChrom = mutate(wspMutacji, nowyChrom)
return nowyChrom
def updateMap(data, map, mapForAstar, regals):
data.mapa = map
znajdzUnbox(data, map)
data.zajeteRegaly = znajdzBox(map, regals)
data.astarMap = data.genMap(mapForAstar)
def mutate(wspMutacji, chrom):
ileWChrom = len(chrom)
ileZmian = round(ileWChrom * wspMutacji)
for i in range(ileZmian):
pom = None
pierw = random.randint(0,ileWChrom - 1)
drug = random.randint(0,ileWChrom - 1)
pom = chrom[pierw]
chrom[pierw] = chrom[drug]
chrom[drug] = pom
return chrom

1
genetyczny/genetyczny.py Normal file
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@ -0,0 +1 @@

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@ -34,7 +34,7 @@ def main():
""" """
if good: if good:
szerokosc = 15#min 6 szerokosc = 15#min 6
wysokosc = 8 #min 7 wysokosc = 10 #min 7
kruche = 1 kruche = 1
latwopalne = 1 latwopalne = 1
radioaktywne = 1 radioaktywne = 1

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@ -58,12 +58,9 @@ class MainWindow:
self.map[i][j] = Shelf(self.screen, self.cell, i, j, (self.map[i][j]-3)%4, (self.map[i][j]-3)//4) self.map[i][j] = Shelf(self.screen, self.cell, i, j, (self.map[i][j]-3)%4, (self.map[i][j]-3)//4)
self.mapForAStar[i][j] = 1 self.mapForAStar[i][j] = 1
self.map = randomBox(self.map, self.regals, 10) self.map = randomBox(self.map, self.regals, 25)
self.data.mapa = self.map updateMap(self.data, self.map, self.mapForAStar, self.regals)
znajdzUnbox(self.data,self.map) generateGeny(self.data)
self.data.zajeteRegaly = znajdzBox(self.map, self.regals)
tmp = self.mapForAStar[:]
self.data.astarMap = self.data.genMap(tmp)
################################################# #################################################
@ -95,7 +92,18 @@ class MainWindow:
print("eee") print("eee")
""" """
elif(event.type==pygame.KEYDOWN): elif(event.type==pygame.KEYDOWN):
populacja = generatePopulation(self.data, self.data.astarMap, [self.wheel.ns, self.wheel.we], 100)
self.data.kordyWozka = (self.wheel.ns, self.wheel.we)
self.data.jakLiczycKoszt = 1
randomPopulation = genRandomPopulation(self.data, 5)
for i in range(100):
if i == 0:
best2 = dwieNajlepsze(randomPopulation, self.data)
else:
x = genPopulacje(best2[0], best2[1], 5, 0.2, 0.3)
best2 = dwieNajlepsze(x, self.data)
self.data.histZmian.append(self.data.best[1])
if len(self.moves)==0: if len(self.moves)==0:
self.wheel.move(event, self.map) self.wheel.move(event, self.map)
elif(event.type==pygame.MOUSEBUTTONDOWN): elif(event.type==pygame.MOUSEBUTTONDOWN):