File size: 3,481 Bytes
ae4627d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 | import copy, random
from schedule import Schedule
from utils import bestSolution
from printer import pprint, BLUE
class Optimizer(object):
def __init__(self, plant, orderList, simulator, evaluator):
assert plant != None
assert orderList != None
self.plant = plant
self.orderList = orderList
self.simulator = simulator
self.evaluator = evaluator
self.printing = True
# self.populationSize = 20
self.populationSize = 10
self.indivMutationRate = 0.5
self.selectionRate = 0.5
self.mutationRange = 100
# self.iterations = 25
self.iterations = 20
def run(self):
pprint("OPT calculating initial population...", BLUE, self.printing)
population = self.initialPopulation()
for i in range(self.iterations):
pprint("OPT iteration number %s" % (i + 1), BLUE, self.printing)
population = self.mutatePopulation(population)
print bestSolution(population)
def calcIndividualFitness(self, indiv):
self.simulator.simulate(indiv)
self.evaluator.evaluate(indiv)
def sortPopulation(self, population):
population.sort(lambda a, b: cmp(b.fitness, a.fitness))
def mutatePopulation(self, population):
for i in range(int(self.selectionRate * len(population))):
mutatedIndiv = self.mutateIndividual(population[i])
while self.isIndividualInPopulation(mutatedIndiv, population) == True:
mutatedIndiv = self.mutateIndividual(population[i])
self.calcIndividualFitness(mutatedIndiv)
population.append(mutatedIndiv)
self.sortPopulation(population)
return population[:self.populationSize]
def isIndividualInPopulation(self, individual, population):
for i in population:
if i == individual:
return True
return False
def initialPopulation(self):
population = []
initIndiv = self.initialIndividual()
population.append(initIndiv)
for i in range(self.populationSize):
pprint("OPT generating new initial individual...", BLUE, self.printing)
mutatedIndiv = self.mutateIndividual(initIndiv)
while self.isIndividualInPopulation(mutatedIndiv, population) == True:
mutatedIndiv = self.mutateIndividual(initIndiv)
pprint("OPT calculating fitness of individual...", BLUE, self.printing)
self.calcIndividualFitness(mutatedIndiv)
pprint("OPT Done.", BLUE, self.printing)
population.append(mutatedIndiv)
self.sortPopulation(population)
return population
def mutateIndividual(self, originalIndiv):
newIndiv = copy.deepcopy(originalIndiv)
newIndiv.schedule = []
newIndiv.finishTimes = []
indivLen = len(newIndiv.startTimes)
assert indivLen == len(self.orderList.orders)
indexes = range(indivLen)
for i in range(int(self.indivMutationRate * indivLen)):
index = int(random.uniform(0, len(indexes)))
newIndiv.startTimes[indexes[index]][2] = \
self.mutateGene(newIndiv.startTimes[indexes[index]][2])
del indexes[index]
return newIndiv
def mutateGene(self, value):
addent = int(random.uniform(0, self.mutationRange))
if (random.uniform(0, 1) < 0.5):
addent = -addent
return max(0, value + addent)
def initialIndividual(self):
indiv = Schedule()
for o in self.orderList.orders:
if o.currentMachine == "":
minProcTime = o.recipe.calcMinProcTime(self.plant)
machineName = o.recipe.recipe[0][0]
else:
machineName = o.currentMachine
minProcTime = o.recipe.calcMinProcTime(self.plant, o.currentMachine)
indiv.startTimes.append(
[o, str(machineName), max(0, o.deadline - minProcTime)])
return indiv
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