def main():
ClockProcess().start() # 开启一个子进程，用于获取所有需解析的URL,并存储到数据库
PutUrlToQueue(Wanfang, 20) # 往队列queue放20条数据，进行数据待处理
LoopTimer(0.5, PutUrlToQueue, args=(
Wanfang,
20,
)).start() # 开启一个线程，比如Thread-7,它会0.5秒执行一下PutUrlToList函数
count=100,
retain_rate=0.25,
random_select_rate=0.5,
mutation_rate=0.05,
section_id=sec_id)
fig = plt.figure(num="遗传算法")
x, y = [], []
for i in range(70):
ga.evolve()
solution, seq, average_volume = ga.sloution()
mytest = "the %d iter: %s %s" % (i, average_volume, seq)
log.write_textctrl_txt(mytest)
print("the %d iter:" % i, average_volume, seq)
x.append(i + 1)
y.append(average_volume)
solution, seq, average_volume = ga.sloution()
# PutData(solution, sec_id).convert_package()
plt.plot(x, y)
plt.title("遗传算法——随机选纸箱迭代结果图", fontproperties=simsun)
plt.xlabel("迭代次数", fontproperties=simsun)
plt.ylabel("纸箱体积平均利用率", fontproperties=simsun)
plt.show()
else:
print("{} No section is needed to pack.".format(current_time()))
if __name__ == '__main__':
loop = LoopTimer(interval=2, target=CartonPackAlgorithmMain)
loop.start()
loop.join()
pc_low, pc_up = 0.6, 0.99
pm_low, pm_up = 0.05, 0.6
beta = 0.01
if i != 0:
if y[i - 1] == y[i]:
unevolveNum += 1
else:
unevolveNum = 0
else:
unevolveNum = 0
ga.crossRate = pc_low + (pc_up - pc_low) * (1 - math.exp(
-beta * unevolveNum)) / (1 + math.exp(-beta * unevolveNum))
ga.mutation_rate = pm_low + (pm_up - pm_low) * (1 - math.exp(
-beta * unevolveNum)) / (1 + math.exp(-beta * unevolveNum))
end_time = time.time()
print('算法迭代所花费的时间为：%s' % (end_time - start_time))
print(ga._boxes)
# LayoutGraph(solution)
# Graph().pltIterGraph(x, (y,), name)
Graph().pltIterGraph(
x, (y, crossRates, mutateRates, volumeRate, end_time - start_time),
name,
mod=1)
if __name__ == '__main__':
loop = LoopTimer(interval=2, target=Instance1Main)
loop.start()
loop.join()
self.plate_temp[current_level_next][2] = self.layout_component_info[r][0] - get_x
current_level_next = self.get_new_plate_info(current_level_next, get_x)
i = r - 1
break
elif r == len(self.layout_component_info) - 1 and self.layout_component_info[r][1] == self.lowest_level_line:
self.plate_temp[current_level_next][2] = self._box_long - get_x
current_level_next = self.get_new_plate_info(current_level_next, get_x)
i = r
break
i += 1
return current_level_next
def get_new_plate_info(self, current_level_next, _x):
self.plate_temp[current_level_next][0] = _x
self.plate_temp[current_level_next][1] = self.lowest_level_line
self.plate_temp[current_level_next][3] = self._box_short - self.lowest_level_line
current_level_next += 1
return current_level_next
def get_time():
t = time.strftime('%Y{y}%m{m}%d{d} %H{h}%M{f}%S{s}').format(y=u'年', m=u'月', d=u'日', h=u'时', f=u'分', s=u'秒')
return t
if __name__ == '__main__':
pack = CardBoardPack()
loop = LoopTimer(interval=2, target=pack.package_main)
loop.start()
loop.join()
ga = GA(sec_id, partList, box, len(partList))
for i in range(500):
ga.evolve()
solution, seq, volumeRate = ga.getSolution()
crossRates.append(ga.crossRate)
mutateRates.append(ga.mutation_rate)
iterTimes.append(i+1)
volumeRates.append(volumeRate)
print("the %d iter:" % (i + 1), volumeRate, crossRates[i], mutateRates[i])
if volumeRate == bestTarget:
break
algo_time = time.time() - start_time
print('算法迭代所花费的时间为：%s' % algo_time)
resSol = PutData(solution, sec_id, volumeRates[-1]).decodeSol()
saveIterData(iterTimes, volumeRates, crossRates, mutateRates, algo_time, resSol, setName)
Graph().pltIterGraph(iterTimes,(volumeRates,crossRates,mutateRates,volumeRate,algo_time),setName,mod=0)
LayoutGraph(resSol)
if __name__ == '__main__':
if runMode == 0:
loop = LoopTimer(interval=2, target=mainAGA)
loop.start()
loop.join()
elif runMode == 1:
mainAGA()
else:
raise AttributeError("The run mode must be 0 or 1.")