def cal_mat_priority(self, now_time):
# 计算 rest剩余未完成量、(now_time-last_time)距离上次plan_day修改时间、（仓库合理工作强度-当前车辆工作数）的softmax函数
rest_list = list()
time_list = list()
cars_num_list = list()
for warehouse in self.__warehouse_list:
for mat in warehouse.get_mat_list():
rest_list.append(mat.get_rest())
time_list.append(
int((Tool.string_to_datetime(now_time) -
Tool.string_to_datetime(
mat.get_last_time())).total_seconds()))
cars_num_list.append(warehouse.get_rea() - warehouse.get_act())
rest = Tool.softmax(rest_list)
last_time = Tool.softmax(time_list)
cars_num = Tool.softmax(cars_num_list)
# 计算优先级
index = 0
for i in range(len(self.__warehouse_list)):
priority_list = list()
for j in range(len(self.__warehouse_list[i].get_mat_list())):
if cars_num[i] == 0:
priority_list.append(0)
else:
priority_list.append(
(rest[index] * last_time[index]) / cars_num[index])
index += 1
self.__warehouse_list[i].set_mat_priority(priority_list)
print(priority_list)
def cars_init(self, cars_list):
new_cars_list = cars_list
for car in new_cars_list:
car.set_finish_time(Tool.datetime_to_string(Tool.string_to_datetime(car.get_entry_time()) + datetime.timedelta(seconds=self.__unloadTime)))
if car.get_finish_time() < '2019-10-25 00:00:00':
car.set_finish_time('2019-10-25 00:00:00')
return new_cars_list
def ready_cars_init(self, cars_list):
# 准备车辆也确定了进厂时间和离厂时间
new_cars_list = cars_list
for car in new_cars_list:
for warehouse in self.__inFactory.get_warehouse():
if car.get_target_warehouse() == warehouse.get_warehouse_code(
):
car.set_entry_time(
Tool.datetime_to_string(
Tool.string_to_datetime(car.get_notice_time()) +
datetime.timedelta(
seconds=warehouse.get_preTime())))
if car.get_entry_time() < '2019-10-25 00:00:00':
car.set_entry_time('2019-10-25 00:00:00')
car.set_finish_time(
Tool.datetime_to_string(
Tool.string_to_datetime(car.get_entry_time()) +
datetime.timedelta(
seconds=warehouse.get_unloadTime())))
return new_cars_list
def cal_cars_priority(self, now_time):
time_list = list()
mat_priority = list()
# 计算每个车辆已等时间的softmax函数
for car in self.__queue_cars:
time_list.append(
int((Tool.string_to_datetime(now_time) -
Tool.string_to_datetime(
car.get_queue_start_time())).total_seconds()))
time_result = Tool.softmax(time_list)
# 计算每个仓库中品种优先级的softmax函数
for warehouse in self.__inFactory.get_warehouse():
for mat in warehouse.get_mat_list():
mat_priority.append(mat.get_priority())
priority_result = Tool.softmax(mat_priority)
# 计算每辆车得优先级
for i in range(len(self.__queue_cars)):
count = int() # 用于保存多个仓库的优先级*权重之和
# 遍历car的每个目的仓库
for warehouse1 in self.__queue_cars[i].get_target_warehouse():
index = 0
# 遍历厂内所有仓库，目的是找出仓库内品种的优先级
for warehouse2 in self.__inFactory.get_warehouse():
# 如果相等则匹配到了
if warehouse1 == warehouse2.get_warehouse_code():
# 遍历仓库内所有品种，目的是找出仓库内和车辆相同的品种
for mat in warehouse2.get_mat_list():
# 物料名和小品种要都相等才能确定
if mat == self.__queue_cars[i].get_mat_code() \
and self.__queue_cars[i].get_sub_kind_name() == mat.get_sub_kind_name():
count += priority_result[index]
break
index += 1
break
else:
index += len(warehouse2.get_mat_list())
x = time_result[i] * (
count / len(self.__queue_cars[i].get_target_warehouse()))
self.__queue_cars[i].set_priority(x)
print(x)
def data_analyse4(data):
result = list()
hour = datetime.timedelta(hours=1)
half_hour = datetime.timedelta(minutes=30)
time = '2019-10-25 00:00:00'
while time != '2019-11-29 00:00:00':
for warehouse in warehouse_code:
num = len(data[(data['WAREHOUSE_CODE'] == warehouse)
& (data['ENTRY_TIME'] < time)
& (data['FINISH_TIME'] > time)])
warehouse_dict[warehouse].append(num)
# print(warehouse, '在', time, '的时候有', num, '辆车')
time = tool.datetime_to_string(tool.string_to_datetime(time) + hour)
for warehouse in warehouse_code:
j = 0
for i in range(len(warehouse_dict[warehouse])):
if warehouse_dict[warehouse][j] == 0:
warehouse_dict[warehouse].pop(j)
else:
j += 1
temp = list()
temp.append(warehouse)
temp.append(stats.mode(warehouse_dict[warehouse])[0][0])
temp.append(max(warehouse_dict[warehouse]))
# print(warehouse, '的众数是：', stats.mode(warehouse_dict[warehouse])[0][0])
# print(warehouse, '的max是：', max(warehouse_dict[warehouse]))
warehouse_dict[warehouse].sort(reverse=True)
temp.append(
int(
np.mean(warehouse_dict[warehouse]
[0:len(warehouse_dict[warehouse]) // 3 + 1])))
result.append(temp)
# print(warehouse, '的较大值是：', np.mean(warehouse_dict[warehouse][0: len(warehouse_dict[warehouse]) // 3 + 1]))
df = pd.DataFrame(result,
columns=['warehouse_code', 'mode', 'max', 'minorMax'])
df.to_excel('warehouseLimit.xls', index=False)
# import pandas as pd
#
# import demo.setting.Data_acquisition as Data_acquisition
import demo.setting.Tools as Tool
# import ssl
# import demo.OutFactory as OutFactory
# import datetime
import numpy as np
import sklearn.preprocessing as preprocessing
import math
a = int((Tool.string_to_datetime('2019-10-25 11:00:00') -
Tool.string_to_datetime('2019-10-25 10:00:00')).total_seconds())
print(a)
def get_wait_time(self):
return Tool.string_to_datetime(self.__notice_time)-Tool.string_to_datetime(self.__entry_time)
def call(self, time):
car_list = list() # 存储本次叫号的车辆
pre_time = Tool.datetime_to_string(
Tool.string_to_datetime(time) -
datetime.timedelta(seconds=Tool.interval))
# 选取上一个时间段的plan_day
plan_day = self.plan_day[(self.plan_day['update_time'] >= pre_time)
& (self.plan_day['update_time'] <= time)]
# 更新每个仓库内的每个原料的更新时间和剩余未完成量
for warehouse in self.__inFactory.get_warehouse():
for mat in warehouse.get_mat_list():
if mat.get_mat_code() == '11002000010000':
mat_plan_day = plan_day[
(plan_day['sub_kind_name'] == mat.get_sub_kind_name())
& (plan_day['warehouse_code'] == warehouse.
get_warehouse_code())]['add_weight'].tolist()
else:
mat_plan_day = plan_day[
(plan_day['kind_code'] == mat.get_mat_code())
& (plan_day['warehouse_code'] == warehouse.
get_warehouse_code())]['add_weight'].tolist()
if len(mat_plan_day) == 0:
continue
add_weight = int(mat_plan_day[-1])
mat.update(time, add_weight - mat.get_sum())
self.__inFactory.cal_mat_priority(time) # 计算每个原料的优先级
self.cal_cars_priority(time) # 计算每辆车的优先级
self.__queue_cars.sort(key=lambda x: x.get_priority())
# for car in self.__queue_cars:
# for car in self.__queue_cars:
# # 外购废钢看小品名
# if car.get_mat_code() == '11002000010000':
# for warehouse in self.__inFactory.get_warehouse():
# for mat in warehouse.get_mat_list():
# if mat.get_sub_kind_name() == car.get_sub_kind_name():
# if mat.get_rest() > 0:
# car.set_notice_time(time)
# car.set_entry_time(Tool.datetime_to_string
# (Tool.string_to_datetime(car.get_notice_time()) + datetime.timedelta
# (seconds=warehouse.get_preTime())))
# car.set_finish_time(Tool.datetime_to_string
# (Tool.string_to_datetime(car.get_entry_time)) + datetime.timedelta
# (seconds=warehouse.get_unloadTime()))
# mat.add_sum()
# mat.sub_rest()
# car_list.append(car)
# # 其他看物料名
# else:
# for warehouse in self.__inFactory.get_warehouse():
# for mat in warehouse.get_mat_list():
# if mat.get_mat_code() == car.get_mat_code():
# if mat.get_rest() > 0:
# car.set_notice_time(time)
# car.set_entry_time(Tool.datetime_to_string
# (Tool.string_to_datetime(car.get_notice_time()) + datetime.timedelta
# (seconds=warehouse.get_preTime())))
# car.set_finish_time(Tool.datetime_to_string
# (Tool.string_to_datetime(car.get_entry_time)) + datetime.timedelta
# (seconds=warehouse.get_unloadTime()))
# mat.add_sum()
# mat.sub_rest()
# car_list.append(car)
return car_list