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This commit is contained in:
Yofuria 2023-07-25 21:32:08 +08:00
parent 49020043db
commit 1229d9e3c2
15 changed files with 249 additions and 191 deletions
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5
.idea/HTSim.iml
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@ -2,7 +2,10 @@
<module type="PYTHON_MODULE" version="4">
<component name="NewModuleRootManager">
<content url="file://$MODULE_DIR$" />
<orderEntry type="jdk" jdkName="Python 3.10 (2)" jdkType="Python SDK" />
<orderEntry type="jdk" jdkName="C:\Users\Yofuria\miniconda3" jdkType="Python SDK" />
<orderEntry type="sourceFolder" forTests="false" />
</component>
<component name="PyDocumentationSettings">
<option name="renderExternalDocumentation" value="true" />
</component>
</module>

2
.idea/misc.xml
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@ -1,4 +1,4 @@
<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="ProjectRootManager" version="2" project-jdk-name="Python 3.10 (2)" project-jdk-type="Python SDK" />
<component name="ProjectRootManager" version="2" project-jdk-name="C:\Users\Yofuria\miniconda3" project-jdk-type="Python SDK" />
</project>

6
.idea/other.xml Normal file
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@ -0,0 +1,6 @@
<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="PySciProjectComponent">
<option name="PY_SCI_VIEW_SUGGESTED" value="true" />
</component>
</project>

55
Environment.py
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@ -18,7 +18,7 @@ class FMSEnv(ap.Model):
# xv_int_max_order: int
# ev_n_order_created: int
the_firm: Firm
the_firm: Firm # Firm类
# record data, define below
# op_os_n_total_order: int
@ -28,7 +28,7 @@ class FMSEnv(ap.Model):
# op_is_flt_material_room_left: float
# op_is_flt_product_room_left: float
op_ps_str_status: str
op_os_int_status: int
op_os_to_dlv: np.ndarray
op_is_current_product: np.ndarray
op_is_current_material: np.ndarray
@ -39,6 +39,7 @@ class FMSEnv(ap.Model):
op_ip_prd_s: np.ndarray
op_ip_prd_big_s: np.ndarray
op_ip_prd_est_pfm: int
op_os_n_total_order: int
def __init__(self, dct_all_para, _run_id=None):
super().__init__()
@ -47,11 +48,13 @@ class FMSEnv(ap.Model):
self.the_firm = Firm(env=self, dct_all_para=dct_all_para)
# get the input parameter values from the dictionary
self.int_stop_time = int(dct_all_para['time'])
self.int_stop_time = int(dct_all_para['time']) # 停止接单时间
# self.xv_int_max_order = int(dct_all_para['xv_int_max_order'])
self.xv_dlv_product_para = np.asarray(dct_all_para['xv_dlv_product_para'])
# self.xv_dlv_product_para = np.asarray(dct_all_para['xv_dlv_product_para'])
# self.xv_int_dlv_period_lam = int(dct_all_para['xv_int_dlv_period_lam'])
# self.ev_n_order_created = 0
self.op_os_n_total_order = 0
self.op_os_int_status = 0
self.running = True
self.t = 0
@ -62,17 +65,16 @@ class FMSEnv(ap.Model):
xv_int_create_order_num = 1
# xv_int_create_order_num = random.poisson(lam=xv_int_create_order_lam, size=None)
# if self.ev_n_order_created < xv_int_max_order:
for i in range(xv_int_create_order_num):
new_order = Order(model=self, time_created=self.t, xv_dlv_product_para=self.xv_dlv_product_para,
leadtime=max(self.the_firm.xv_ary_lead_time))
# for i in range(xv_int_create_order_num):
new_order = Order(model=self, time_created=self.t)
return new_order
return None
# return None
# Execute the interactions of each time step in the simulation.
def step(self):
# organize the interactions of agents in each time step here
new_order = self.create_order()
self.the_firm.the_os.accept_order(new_order)
new_order = self.create_order() # 接收创建的订单
self.the_firm.the_os.accept_order(new_order=new_order)
self.the_firm.operating()
self.update()
@ -82,16 +84,17 @@ class FMSEnv(ap.Model):
self.stop()
else:
print(f"running the {self.t} step")
print(self.the_firm.the_os.ev_ave_delay_time)
# Record data after each simulation
def update(self):
self.op_os_n_total_order = len(self.the_firm.the_os.a_lst_order)
def update(self): # ?
self.op_os_n_total_order = len(self.the_firm.the_os.a_lst_order) # 订单个数
# self.op_os_n_total_order_delayed = len([e for e in self.the_firm.the_os.a_lst_order if e.xv_dlv_t < self.t])
self.op_os_to_dlv = self.the_firm.the_os.ev_ary_to_dlv
self.op_os_to_dlv = self.the_firm.the_os.ev_ary_to_dlv # 当期及之前未满足需求总和
# self.op_os_all_delay_time = self.the_firm.the_os.ev_lst_all_delay_time
self.op_ps_produced_num = self.the_firm.the_ps.ev_ary_produced_num
self.op_ps_str_status = self.the_firm.the_ps.ev_str_status
self.op_ps_produced_num = self.the_firm.the_ps.ev_ary_produced_num # 当期产品生产数量
self.op_ps_str_status = self.the_firm.the_os.ev_int_produce_type # 当期生产状态
# self.op_is_current_product = self.model.the_firm.the_is.ev_ary_current_product
#
@ -101,13 +104,14 @@ class FMSEnv(ap.Model):
self.op_ps_back_trans_material = self.model.the_firm.the_ps.ev_lst_backtrans_material
self.record([att for att in self.__dict__.keys() if att.startswith('op_')])
pass
self.record([att for att in self.__dict__.keys() if att.startswith('op_')]) # ?
# pass
if __name__ == '__main__':
dct_para = {
'time': 60,
'time': 60, # 进行总时间数
# 'xv_int_max_order': random.randint(30, 50),
# 'xv_dlv_product_para': tuple([(30, 100), (30, 50)]),
# 'xv_dlv_product_para': tuple([30,40,30,20]), # 读取生产率 np.read.
@ -117,11 +121,20 @@ if __name__ == '__main__':
# 'xv_ary_cost_material_per': tuple([0.1,0.1,0.2,0.4]),
# 'xv_ary_volume_material': tuple([1.0, 1.5]),
# 'xv_ary_volume_product': tuple([3.0, 5.0]),
'xv_array_lead_time': 2, # 读取原材料表格 np.read.,暂时不读
# 'xv_array_lead_time': 2, # 读取原材料表格 np.read, 暂时不读 变量代表的含义
# 'xv_int_lead_time_c': 3,
# 'xv_int_lead_time_d': 1,
'xv_ary_initial_product_num': pd.read_excel("initial_product.xlsx").to_numpy(),
'xv_ary_initial_material_num': pd.read_excel("initial_material.xlsx").to_numpy(), # 应读取遗传算法中随机生成的s，暂写为'1' 创建两个excel分别存储产品和原材料的库存 每个excel中存系统代码和库存
'xv_ary_product_id': pd.read_excel("initial_product.xlsx").to_numpy()[:, 0], # 产成品id顺序
'xv_ary_material_id': pd.read_excel("initial_material.xlsx").to_numpy()[:, 0], # 原材料id顺序
'xv_product_num': len(pd.read_excel("initial_product.xlsx").to_numpy()), # 产成品个数
'xv_material_num': len(pd.read_excel("initial_material.xlsx").to_numpy()), # 原材料个数
'xv_ary_initial_product_num': pd.read_excel("initial_product.xlsx").to_numpy(), # 初始产成品库存 23x2
'xv_ary_initial_material_num': pd.read_excel("initial_material.xlsx").to_numpy(), # 初始原材料库存 115x2
'xv_ary_bom': pd.read_excel("bom23.xlsx").to_numpy(), # bom表
'xv_ary_plan': pd.read_excel("plan.xlsx").to_numpy(), # plan表
'xv_ary_s': pd.read_excel("rawmaterial - s.xlsx").to_numpy(), # s
'xv_ary_S': pd.read_excel("rawmaterialS.xlsx").to_numpy(), # S
# 应读取遗传算法中随机生成的s，暂写为'1' 创建两个excel分别存储产品和原材料的库存 每个excel中存系统代码和库存
# 'xv_flt_initial_cash': 50000.0,
# 'dct_status_info': json.dumps({ #需要引入生产状态表
# "0": {"xv_flt_produce_rate": tuple([0.0, 0.0]),

44
Firm.py
View File

@ -5,6 +5,7 @@ from InventorySystem import InventorySystem
from OrderSystem import OrderSystem
from ProduceSystem import ProduceSystem
# Create Company Instance
class Firm:
the_os: OrderSystem
@ -15,23 +16,46 @@ class Firm:
self.env = env
# get the parameters here
self.xv_ary_initial_product_num = np.asarray(dct_all_para['xv_ary_initial_product_num'])
self.xv_ary_initial_material_num = np.asarray(dct_all_para['xv_ary_initial_material_num'])
self.dct_status_info = json.loads(dct_all_para['dct_status_info'])
self.xv_ary_lead_time = np.array([dct_all_para['xv_int_lead_time_a'], dct_all_para['xv_int_lead_time_b']])
self.xv_ary_initial_product_num = np.asarray(dct_all_para['xv_ary_initial_product_num']) # 初始产成品库存
self.xv_ary_initial_material_num = np.asarray(dct_all_para['xv_ary_initial_material_num']) # 初始原材料库存
self.xv_product_num = int(dct_all_para['xv_product_num']) # 产成品个数
self.xv_material_num = int(dct_all_para['xv_material_num']) # 原材料个数
self.xv_ary_plan = np.asarray(dct_all_para['xy_ary_plan'])
self.xv_ary_bom = np.asarray(dct_all_para['xv_ary_bom'])
self.xv_ary_product_id = np.asarray(dct_all_para['xv_ary_product_id'])
self.xv_ary_material_id = np.asarray(dct_all_para['xv_ary_material_id'])
self.xv_ary_s = np.asarray(dct_all_para['xv_ary_s'])
self.xv_ary_S = np.asarray(dct_all_para['xv_ary_S'])
# self.dct_status_info = json.loads(dct_all_para['dct_status_info']) # 生产状态表
# self.xv_ary_lead_time = np.array([dct_all_para['xv_int_lead_time_a'], dct_all_para['xv_int_lead_time_b']])
# create agents here
self.the_os = OrderSystem(env)
self.the_os = OrderSystem(env, xv_produt_num=self.xv_product_num, xv_ary_plan=self.xv_ary_plan,
xv_ary_product_id=self.xv_ary_product_id) # 实例Oss
self.the_is = InventorySystem(env, xv_ary_initial_material_num=self.xv_ary_initial_material_num,
xv_ary_initial_product_num=self.xv_ary_initial_product_num,
xv_ary_lead_time=self.xv_ary_lead_time)
self.the_ps = ProduceSystem(env, dct_status_info=self.dct_status_info)
xv_product_num=self.xv_product_num,
xv_material_num=self.xv_material_num,
xv_ary_bom=self.xv_ary_bom, xv_ary_pan=self.xv_ary_plan,
xv_ary_material_id=self.xv_ary_material_id) # 实例Iss
self.the_ps = ProduceSystem(env, xv_ary_bom=self.xv_ary_bom, xv_ary_plan=self.xv_ary_plan,
xv_product_num=self.xv_product_num,
xv_ary_product_id=self.xv_ary_product_id,
xv_ary_material_id=self.xv_ary_material_id) # 实例Pss
# self.the_fs = FinancialSystem(env, xv_flt_initial_cash=self.xv_flt_initial_cash)
def operating(self):
def operating(self): # 按步骤进行
self.the_os.rank_order()
self.the_os.produce_status()
self.the_is.material_state_to_use()
self.the_is.material_check()
self.the_ps.change_status()
self.the_ps.run_produce()
self.the_os.do_shipment()
self.the_ps.run_produce(ev_lst_trans_quan_material=self.the_is.ev_lst_trans_quan_material,
ev_ary_product_to_produce=self.the_os.ev_ary_product_to_produce)
self.the_is.consume_and_store(ev_ary_produced_num=self.the_ps.ev_ary_produce_number,
ev_changed_product=self.the_os.ev_changed_product,
ev_lst_backtrans_material=self.the_ps.ev_lst_backtrans_material)
self.the_is.material_replenishment()
self.the_os.do_shipment(ev_ary_current_product=self.the_is.ev_ary_current_product)
# self.the_is.inventory_cost()
# self.the_fs.financial_calculating()

140
InventorySystem.py
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@ -1,135 +1,131 @@
import agentpy as ap
import numpy as np
import pandas as pd
from collections import deque
class InventorySystem(ap.Agent):
xv_ary_initial_material_num: np.ndarray
xv_ary_initial_product_num: np.ndarray
ev_ary_current_material: np.ndarray #期末库存
ev_ary_current_product: np.ndarray #期末库存
ev_lst_trans_quan_material: np.ndarray # Iss传递给Pss的原材料数量
ev_lst_backtrans_quan_material: np.ndarray # Pss退回的原材料数量
xv_ary_initial_material_num: np.ndarray # 初始原材料库存
xv_ary_initial_product_num: np.ndarray # 初始产成品库存
ev_ary_current_material: np.ndarray # 当期原材料库存
ev_ary_current_product: np.ndarray # 当期产成品库存
ev_ary_material_state_to_use: np.ndarray # 当期预期使用的原材料
ev_ary_material_to_use: np.ndarray # 当期实际消耗的原材料
xv_array_dlv_product: np.ndarray # 产品交付
ev_ary_is_order_material: np.ndarray # 是否订购产品
ev_ary_num_material_to_order: np.ndarray # 订购数量
ev_ary_num_material_order_done: np.ndarray # 当期送到的数量
# set the lead time of material replenishment
xv_ary_lead_time: np.ndarray
xv_ary_lead_time: np.ndarray # 原材料订货的等待时间
# the list of materials in transit
ev_lst_trans_material: list # Iss交给Pss的原材料
ev_list_back_trans_material: list # Pss返回的原材料
ev_lst_trans_quan_material: list # Iss传递给Pss的原材料数量
ev_lst_backtrans_quan_material: list # Pss退回的原材料数量
ev_lst_material_inventory: list
ev_lst_product_inventory: list
# Material list
xv_lst_material: np.ndarray
xv_ary_material: np.ndarray
xv_ary_bom: np.ndarray
# 原材料订购的开始时间和到达时间
ev_int_order_time: np.ndarray
ev_int_arrive_time: np.ndarray
ev_ary_num_material_order_done: np.ndarray # 当期原材料到货量
ev_ary_order_time: np.ndarray
ev_ary_arrive_time: np.ndarray
def setup(self, xv_ary_initial_material_num,
xv_ary_initial_product_num, xv_ary_lead_time):
xv_product_num: int
xv_material_num: int
xv_ary_plan: np.ndarray
def setup(self, xv_ary_initial_material_num, xv_ary_initial_product_num, xv_product_num, xv_material_num,
xv_ary_bom, xv_ary_plan, xv_ary_material_id):
# Set up the initial inventory quantity
self.xv_ary_initial_material_num = xv_ary_initial_material_num
self.xv_ary_initial_product_num = xv_ary_initial_product_num
self.ev_ary_current_material = xv_ary_initial_material_num # 115*2
self.ev_ary_current_product = xv_ary_initial_product_num #23*2
self.ev_ary_num_material_order_done = np.zeros((115, ))
self.ev_ary_current_product = xv_ary_initial_product_num # 23*2
self.xv_product_num = xv_product_num # 产成品个数
self.xv_material_num = xv_material_num # 原材料个数
self.ev_ary_num_material_order_done = np.zeros((xv_material_num,)) # 当期原材料送到的数量 115x1
# set the lead time of materials
# 读取各个原材料的历史平均交货周期 bom table
self.xv_ary_lead_time = pd.read_excel("bom23.xlsx").iloc[:, 4].to_numpy()
self.xv_ary_lead_time = xv_ary_bom[:, (1, 4)] # 每一种原材料的到货时间（有重复）
# 切换成原材料
self.ev_ary_is_order_material = np.array([False for i in range(115)])
self.ev_ary_num_material_to_order = np.zeros((115,)) # 初始化
self.ev_ary_material_state_to_use = np.zeros((115,))
self.ev_ary_is_order_material = np.array([False for i in range(xv_material_num)]) # 是否订购原材料
self.ev_ary_num_material_to_order = np.zeros((xv_material_num,)) # 原材料订货数量
self.ev_ary_material_state_to_use = np.zeros((xv_material_num,)) # 一个周期内按照设定生产状态完全生产 原材料消耗数量 计划
self.ev_ary_material_to_use = np.zeros((xv_material_num,)) # 当期实际消耗的原材料数量
self.ev_lst_material_inventory = []
self.ev_lst_product_inventory = []
self.xv_ary_material = xv_ary_material_id # 原材料顺序
self.xv_lst_material = pd.read_excel("rawmaterial.xlsx").to_numpy()
self.xv_ary_bom = pd.read_excel("bom23.xlsx").to_numpy()
self.xv_ary_bom = xv_ary_bom # bom表
self.xv_ary_plan = xv_ary_plan # plan表
self.ev_lst_trans_quan_material = [] # Iss传递给Pss的原材料数量
self.ev_lst_backtrans_quan_material = [] # Pss退回的原材料数量
self.ev_int_order_time = np.zeros((115,))
self.ev_int_arrive_time = np.zeros((115,))
self.ev_ary_order_time = np.zeros((xv_material_num,)) # 原材料订货时间戳
self.ev_ary_arrive_time = np.zeros((xv_material_num,)) # 原材料到货时间戳
<<<<<<< HEAD
def material_state_to_use(self, ev_int_produce_type, xv_plan_excel):
# def material_state_to_use(self, ev_int_produce_type, xv_plan_excel):
# # 读取Oss决定的生产状态，根据生产状态所需的原材料进行汇总
# # self. ev_ary_material_state_to_use = np.multiply(self.xv_array_dlv_product, 原材料表 )
# produce_state = ev_int_produce_type # 获取生产状态
def material_state_to_use(self): # 根据生产状态 看生产一个周期需要多少原材料
# 读取Oss决定的生产状态，根据生产状态所需的原材料进行汇总
# self. ev_ary_material_state_to_use = np.multiply(self.xv_array_dlv_product, 原材料表 )
produce_state = ev_int_produce_type # 获取生产状态
=======
def material_state_to_use(self, xv_ary_dlv_product, ev_int_produce_type):
# 读取Oss决定的生产状态，根据生产状态所需的原材料进行汇总
# self. ev_ary_material_state_to_use = np.multiply(self.xv_array_dlv_product, 原材料表 )
produce_state = 1 # 获取生产状态
>>>>>>> 6027857189fa76bd175eb941904972de305532a4
produce_plan = xv_plan_excel[xv_plan_excel[:, 0] == produce_state]
for plan in produce_plan:
produce_state = self.model.the_firm.the_os.ev_int_produce_type # 获取生产状态
produce_plan = self.xv_ary_plan[self.xv_ary_plan[:, 0] == produce_state] # 该生产状态下各产品的生产计划
for product_plan in produce_plan:
for bom in self.xv_ary_bom:
if plan[1] == bom[0]:
self.ev_ary_material_state_to_use[np.where(self.xv_lst_material == bom[1])] += plan[3] * bom[
if product_plan[1] == bom[0]:
self.ev_ary_material_state_to_use[np.where(self.xv_ary_material == bom[1])] += product_plan[3] * \
bom[
2] # 某原材料的生产数量加等产品生产量乘单位原材料消耗量
def material_check(self, ev_ary_material_state_to_use):
def material_check(self): # 检查库存是否充足
# 根据Iss决策，核对库存是否充足，并将拥有的原材料交给Pss
# 可能需要一部生成原材料列表在调用
# Check whether materials are enough and transfer material
index_mapping = {value: idx for idx, value in enumerate(self.ev_ary_current_material[:, 0])}
sorted_indices = [index_mapping[value] for value in self.xv_lst_material]
self.ev_ary_current_material = self.ev_ary_current_material[sorted_indices] # 按照原材料制定顺序进行重排
for i in range(115):
if self.ev_ary_current_material[i, 1] >= ev_ary_material_state_to_use[i]:
self.ev_lst_trans_quan_material[i] = ev_ary_material_state_to_use[i]
# return (self.ev_ary_current_material >= ev_ary_material_to_use).all()
else:
self.ev_lst_trans_quan_material[i] = self.ev_ary_current_material[i]
for i in range(self.xv_material_num):
self.ev_lst_trans_quan_material[i] = min(self.ev_ary_current_material[i, 1],
self.ev_ary_material_state_to_use[i]) # 需要数量和库存两者间的较小值
# if self.ev_ary_current_material[i, 1] >= ev_ary_material_state_to_use[i]: # 库存足够按照计划生产
# self.ev_lst_trans_quan_material[i] = ev_ary_material_state_to_use[i]
# else:
# self.ev_lst_trans_quan_material[i] = self.ev_ary_current_material[i]
def consume_and_store(self, ev_ary_material_to_use, ev_ary_produced_num,ev_changed_product,
def consume_and_store(self, ev_ary_produced_num, ev_changed_product,
ev_lst_backtrans_material):
self.ev_lst_backtrans_quan_material = ev_lst_backtrans_material
self.ev_lst_backtrans_quan_material = ev_lst_backtrans_material # Pss传回的原材料数量
# Update the inventory after production
for i in range(115):
for i in range(self.xv_material_num):
self.ev_ary_material_to_use[i] = self.ev_lst_trans_quan_material[i] - \
self.ev_lst_backtrans_quan_material[i]
if self.ev_int_arrive_time == self.model.t: # 判断材料是否到达
self.ev_ary_num_material_order_done[i] += self.ev_ary_num_material_to_order[i]
if self.ev_ary_arrive_time[i] == self.model.t: # 判断材料是否到达
self.ev_ary_current_material[i, 1] = self.ev_ary_current_material[i, 1] - self.ev_ary_material_to_use[i] \
+ self.ev_ary_num_material_to_order[i] # 减消耗量 加订购量
self.ev_ary_num_material_to_order[i] = 0
self.ev_ary_is_order_material[i] = False
self.ev_ary_current_material = self.ev_ary_current_material - ev_ary_material_to_use \
+ self.ev_ary_num_material_order_done
self.ev_ary_current_product = ev_changed_product + ev_ary_produced_num
return self.ev_ary_current_material, self.ev_ary_current_product
self.ev_ary_current_product[:, 1] = ev_changed_product + ev_ary_produced_num[:, 1] # 上期期末加本期生产
def material_replenishment(self):
# return self.ev_ary_current_material, self.ev_ary_current_product
def material_replenishment(self, xv_ary_s, xv_ary_S):
# Check the inventory of material to decide whether to replenish
# 核对原材料数量是否低于s
# 带时间戳
for i in range(115):
if self.ev_ary_current_material[i] <= s:
for i in range(self.xv_material_num):
if self.ev_ary_current_material[i, 1] <= xv_ary_s[i, 1] and self.ev_ary_is_order_material[i] == False:
self.ev_ary_is_order_material[i] = True
self.ev_ary_num_material_to_order[i] = S - self.ev_ary_current_material[i]
self.ev_int_order_time[i] = self.model.t
self.ev_int_arrive_time[i] = self.ev_int_order_time[i] + \
self.xv_ary_bom[self.xv_ary_bom[:, 1] == self.xv_lst_material[i]][0, 4]
self.ev_ary_num_material_to_order[i] = xv_ary_S[i, 1] - self.ev_ary_current_material[i, 1]
self.ev_ary_order_time[i] = self.model.t
self.ev_ary_arrive_time[i] = self.ev_int_order_time[i] + self.xv_ary_lead_time[
self.xv_ary_lead_time[:, 0] == self.ev_ary_current_material[i, 0]][0, 1]
else:
self.ev_ary_num_material_to_order[i] = 0

15
Order.py
View File

@ -6,7 +6,6 @@ import pandas as pd
class Order(ap.Agent):
xv_time_created: int # 订单创建时间
xv_time_circle: int # 随机生成的交货周期
xv_dlv_t: int # 客户希望的交货时间
@ -14,22 +13,20 @@ class Order(ap.Agent):
ev_is_delivered: bool # 订单是否已交付
ev_is_accepted: bool # 订单是否被接受
ev_int_delay_time: int # total delay time
ev_int_delay_time: int # 订单延迟交付时间
xv_ary_dlv_product: np.ndarray
ev_ary_dlv_product: np.ndarray
def setup(self, time_created):
self.xv_time_created = time_created
self.xv_time_created = time_created # 订单创建时间
# read the demand of 23 productions
df = pd.read_excel("demand23.xlsx")
self.xv_ary_dlv_product = df.to_numpy()
df = df.iloc[:, 1]
self.ev_ary_dlv_product = df.to_numpy()
self.xv_ary_dlv_product = pd.read_excel("demand23.xlsx").to_numpy() # 接神经网络结果
self.ev_ary_dlv_product = pd.read_excel("demand23.xlsx").to_numpy()[:, 1] # 23x1 把产品的顺序按照xv_ary_product_id重新排列!!!
self.xv_time_circle = np.random.randint(7, 11, 1)
self.xv_dlv_t = self.xv_time_created + self.xv_time_circle
self.xv_dlv_t = self.xv_time_created + self.xv_time_circle # 随机生成期望交付时间
self.ev_actual_dlv_t = self.xv_dlv_t
self.ev_int_delay_time = self.ev_actual_dlv_t - self.xv_dlv_t
self.ev_int_delay_time = 0
# Set the initial status of order to be undelivered, accepted
self.ev_is_delivered = False

68
OrderSystem.py
View File

@ -3,31 +3,34 @@ import numpy as np
from Order import Order
import pandas as pd
# 输出一个生产状态指令，一个交付情况，一个延期时间计算
class OrderSystem(ap.Agent):
a_lst_order: ap.AgentList[Order]
ev_int_produce_type: int
ev_ary_to_dlv: np.ndarray # 当前order list内所有产品的综合
ev_ary_product_to_produce: np.ndarray # 用于计算 production gap
ev_lst_all_delay_time: list
ev_ave_delay_time: float
xv_plan_excel: np.ndarray
ev_lst_flag: list
xv_ary_plan: np.ndarray
ev_changed_product: np.ndarray
xv_product_num: int
xv_ary_product: np.ndarray
# ev_ary_dlv_product: np.ndarray??????
def setup(self):
def setup(self, xv_product_num, xv_ary_plan, xv_ary_product_id):
# Create a list of order
self.a_lst_order = ap.AgentList(self, [])
self.ev_ary_to_dlv = np.zeros((23, 1))
self.ev_int_produce_type = 0
self.ev_ary_product_to_produce = np.zeros((23,))
self.ev_lst_all_delay_time = []
self.a_lst_order = ap.AgentList(self, []) #
self.ev_ary_to_dlv = np.zeros((xv_product_num,))
self.ev_int_produce_type = 0 # 生产状态（方案）
self.ev_ary_product_to_produce = np.zeros((xv_product_num,))
self.ev_ave_delay_time = 0
# self.ev_ary_dlv_product = np.zeros((23,)) ????
self.ev_changed_product = np.zeros((23, ))
self.xv_plan_excel = pd.read_excel("plan.xlsx").to_numpy()
pass
self.ev_changed_product = np.zeros((xv_product_num,))
self.xv_ary_plan = xv_ary_plan
self.xv_product_num = xv_product_num
self.xv_ary_product = xv_ary_product_id
def accept_order(self, new_order):
# Determine whether the order is received and all are currently received
@ -37,67 +40,66 @@ class OrderSystem(ap.Agent):
def rank_order(self):
# Sort order
self.a_lst_order = self.a_lst_order.sort('xv_dlv_t', reverse=False)
self.a_lst_order = self.a_lst_order.sort('xv_dlv_t', reverse=False) # 按预期交付时间排序
def produce_status(self):
# 计算a_lst_order内所有订单包含的产品总量与当期库存的gap，排序最大缺口量，选定生产状态
self.ev_ary_to_dlv = np.zeros((23,))
for order in self.model.the_firm.the_os.a_lst_order:
self.ev_ary_to_dlv = np.zeros((self.xv_product_num,)) # 产品需求总和
for order in self.a_lst_order:
self.ev_ary_to_dlv += order.ev_ary_dlv_product # 当前天之前所有的还未满足的需求求和
self.ev_ary_product_to_produce[:, 1] = self.ev_ary_to_dlv - self.model.the_firm.the_is.ev_ary_current_product
self.ev_ary_product_to_produce = self.ev_ary_to_dlv - self.model.the_firm.the_is.ev_ary_current_product[:, 1]
# self.ev_ary_product_to_produce = self.model.the_firm.the_is.ev_ary_current_product - self.ev_ary_to_dlv
# self.ev_ary_product_to_produce > 0:
# 选出这些产品，按照数值大小进行分类，数值最大的产品对应的能带来最大生产率的状态，则选定为ev_int_produce_type
# 如果均<=0, 按照产品库存ev_ary_current_material进行排序，选择能给库存最低的产品带来最高生产率的状态
sorted_indices = np.argsort(self.ev_ary_product_to_produce[:, 1])[::-1]
sorted_data = self.ev_ary_product_to_produce[sorted_indices]
if sorted_data[0, 1] > 0: # 判断是否存在库存不足
sorted_indices = np.argsort(self.ev_ary_product_to_produce)[::-1]
sorted_data = self.xv_ary_product[sorted_indices] # gap从大到小的产品id
gap_sorted = self.ev_ary_product_to_produce[sorted_indices]
if gap_sorted[0] > 0: # 判断是否存在库存不足
pass
else:
sorted_indices = np.argsort(self.model.the_firm.the_is.ev_ary_current_product[:, 1]) # 对库存进行从小到大排序
sorted_data = self.model.the_firm.the_is.ev_ary_current_product[sorted_indices]
sorted_data = self.model.the_firm.the_is.ev_ary_current_product[:, sorted_indices][:, 0] # 库存从小到大的产品id
a = self.xv_plan_excel[self.xv_plan_excel[:, 1] == sorted_data[0, 0]] # 检索最大值的产品的四种方案或者最小库存产品的四种方案
sorted_indices = np.argsort(a[:, 3])[::-1]
sorted_data = a[sorted_indices]
# return sorted_data[0, 0]
option = self.xv_ary_plan[self.xv_ary_plan[:, 1] == sorted_data[0]] # 检索最大值的产品的四种方案或者最小库存产品的四种方案
sorted_indices = np.argsort(option[:, 3])[::-1]
sorted_data = option[sorted_indices]
self.ev_int_produce_type = sorted_data[0, 0]
return self.ev_int_produce_type
# return self.ev_int_produce_type
def do_shipment(self,ev_ary_current_product):
def do_shipment(self, ev_ary_current_product):
# Make shipments based on ranked order list
# 交付两次，第一次未交付完成的订单要标记，交货的时候先便利delay的订单，如果能够满足全部剩余量，就交货，如果不能
# 就继续在列表中存在
# 只有完全交付的订单，才计算delay time = order.ev_int_delay_time * 第二次交付的订单内的各类产品之和
# 需要更新 order.ev_ary_dlv_product
# Make shipments based on ranked order list
self.ev_lst_all_delay_time = []
self.ev_ave_delay_time = 0
self.ev_changed_product = ev_ary_current_product # 23x1 ndarray 存储本次库存的改变
self.ev_changed_product = ev_ary_current_product[:, 1] # 23x1 ndarray 存储本次库存的改变
for order in self.a_lst_order:
if order.xv_dlv_t == self.model.t: # 第一次交付
# Check and make shipment
order.ev_is_delivered = True
for i in range(len(order.ev_ary_dlv_product)):
for i in range(self.xv_product_num):
if order.ev_ary_dlv_product[i] <= self.ev_changed_product[i]:
order.ev_ary_dlv_product[i] = 0
self.ev_changed_product[i] -= order.ev_ary_dlv_product[i]
order.ev_ary_dlv_product[i] = 0
else:
order.ev_is_delivered = False
elif order.xv_dlv_t < self.model.t and order.ev_is_delivered == False: # 第二次交付
order.ev_is_delivered = True
for i in range(len(order.ev_ary_dlv_product)):
for i in range(self.xv_product_num):
if order.ev_ary_dlv_product[i] > self.ev_changed_product[i]: # 先判断能不能一次性交付
order.ev_is_delivered = False
if order.ev_is_delivered: # 如果一次性交付
delay_num = np.sum(order.ev_ary_dlv_product)
order.ev_ary_dlv_product = np.zeros((23,))
self.ev_changed_product = self.ev_changed_product - order.ev_ary_dlv_product
order.ev_ary_dlv_product = np.zeros((self.xv_product_num,))
order.ev_actual_dlv_t = self.model.t
order.ev_int_delay_time = order.ev_actual_dlv_t - order.xv_dlv_t
self.ev_ave_delay_time += order.ev_int_delay_time * delay_num / 10000
return self.ev_changed_product, self.ev_ave_delay_time
# return self.ev_changed_product, self.ev_ave_delay_time

71
ProduceSystem.py
View File

@ -4,57 +4,74 @@ import random
class ProduceSystem(ap.Agent):
ev_str_status: str # 0,6,8,10 pp_id
ev_str_status: int # 0,6,8,10 pp_id
ev_lst_backtrans_material: list # 退回Iss的原材料
ev_ary_produce_number: np.ndarray
def setup(self, dct_status_info):
self.ev_str_status = 0
xv_ary_bom: np.ndarray
xv_ary_plan: np.ndarray
xv_product_num: int
ev_ary_product: np.ndarray
xv_ary_material: np.ndarray
def setup(self, xv_ary_bom, xv_ary_plan, xv_product_num, xv_ary_product_id, xv_ary_material_id):
self.ev_str_status = 0 # 设置初始生产状态
self.ev_lst_backtrans_material = []
self.ev_ary_produce_number = np.zeros((xv_product_num, 2))
self.xv_ary_bom = xv_ary_bom
self.xv_ary_plan = xv_ary_plan
self.xv_product_num = xv_product_num
self.ev_ary_product = xv_ary_product_id
self.xv_ary_material = xv_ary_material_id
def change_status(self):
self.ev_str_status = self.model.the_firm.the_os.produce_status()
self.ev_str_status = self.model.the_firm.the_os.ev_int_produce_type
def run_produce(self, ev_lst_material, ev_lst_trans_quan_material, ev_ary_product_to_produce, xv_plan_excel,
xv_ary_bom): # ev_ary_product_to_produce 是 需求和库存的gap 23x2
def run_produce(self, ev_lst_trans_quan_material,
ev_ary_product_to_produce): # ev_ary_product_to_produce 是 需求和库存的gap 23x1
# 生产状态由Iss确定，这个函数需要计算生产数量和原材料消耗量。
# 如果原材料不足，就按照production gap(ev_ary_product_to_produce) 大小进行生产；如果没有gap的产品了，就按照库存水平由少到多进行生产。
# 输出生产结果和原材料消耗结果
produce_plan = xv_plan_excel[xv_plan_excel[:, 0] == self.ev_str_status]
sorted_indices = np.argsort(ev_ary_product_to_produce[:, 1])[::-1]
produce_plan = self.xv_ary_plan[self.xv_ary_plan[:, 0] == self.ev_str_status] # 当前生产状态下的产品生产速度
sorted_indices = np.argsort(ev_ary_product_to_produce)[::-1]
sorted_data = ev_ary_product_to_produce[sorted_indices] # 对gap进行从大到小排序
self.ev_ary_product = self.ev_ary_product[sorted_indices]
sorted_indices_product = np.argsort(self.model.the_firm.the_is.ev_ary_current_product[:, 1]) # 对库存进行从小到大排序
sorted_data_product = self.model.the_firm.the_is.ev_ary_current_product[sorted_indices_product]
self.ev_lst_backtrans_material = ev_lst_trans_quan_material
self.ev_ary_produce_number = []
for product in sorted_data:
if product[1] > 0: # gap存在
product_material = xv_ary_bom[xv_ary_bom[:, 0] == product[0]]
produce_number = produce_plan[produce_plan[:, 1] == product[0]][3]
sorted_data_product = self.model.the_firm.the_is.ev_ary_current_product[:, sorted_indices_product]
self.ev_lst_backtrans_material = ev_lst_trans_quan_material # 存储退回给Iss的原材料
self.ev_ary_produce_number = np.zeros((self.xv_product_num, 2))
produce_number_lst = []
for i in range(self.xv_product_num):
if sorted_data[i] > 0: # gap存在
product_material = self.xv_ary_bom[self.xv_ary_bom[:, 0] == self.ev_ary_product[i]]
produce_number = produce_plan[produce_plan[:, 1] == self.ev_ary_product[i]][3]
for material in product_material:
produce_number = min(produce_number, int(
self.ev_lst_backtrans_material[np.where(ev_lst_material == material[1])] / material[
self.ev_lst_backtrans_material[np.where(self.xv_ary_material == material[1])] / material[
2])) # 取能生产的最小个数
for material in product_material:
self.ev_lst_backtrans_material[np.where(ev_lst_material == material[1])] -= produce_number * material[
self.ev_lst_backtrans_material[np.where(self.xv_ary_material == material[1])] -= produce_number * \
material[
2] # 更新原材料消耗情况
self.ev_ary_produce_number.append([product[0], produce_number])
sorted_data_product = sorted_data_product[sorted_data_product[:, 0] != product[0]]
produce_number_lst.append([self.ev_ary_product[i], produce_number])
sorted_data_product = sorted_data_product[sorted_data_product[:, 0] != self.ev_ary_product[i]]
else:
for current_product in sorted_data_product:
product_material = xv_ary_bom[xv_ary_bom[:, 0] == current_product[0]]
product_material = self.xv_ary_bom[self.xv_ary_bom[:, 0] == current_product[0]]
produce_number = produce_plan[produce_plan[:, 1] == current_product[0]][3]
for material in product_material:
produce_number = min(produce_number, int(
self.ev_lst_backtrans_material[np.where(ev_lst_material == material[1])] / material[
self.ev_lst_backtrans_material[np.where(self.xv_ary_material == material[1])] / material[
2])) # 取能生产的最小个数
for material in product_material:
self.ev_lst_backtrans_material[np.where(ev_lst_material == material[1])] -= produce_number * \
material[2] # 更新原材料消耗情况
self.ev_ary_produce_number.append([current_product[0], produce_number])
self.ev_lst_backtrans_material[
np.where(self.xv_ary_material == material[1])] -= produce_number * \
material[
2] # 更新原材料消耗情况
produce_number_lst.append([current_product[0], produce_number])
break
self.ev_ary_produce_number = np.array(self.ev_ary_produce_number)
self.ev_ary_produce_number = np.array(produce_number_lst)
return self.ev_ary_produce_number, self.ev_lst_backtrans_material
# return self.ev_ary_produce_number, self.ev_lst_backtrans_material

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