From 1229d9e3c20e00c46b07b0f0054719fd191c3c12 Mon Sep 17 00:00:00 2001 From: Yofuria <20377277@buaa.edu.cn> Date: Tue, 25 Jul 2023 21:32:08 +0800 Subject: [PATCH] update --- .idea/HTSim.iml | 5 +- .idea/misc.xml | 2 +- .idea/other.xml | 6 ++ Environment.py | 57 ++++++++++------ Firm.py | 44 +++++++++--- InventorySystem.py | 154 ++++++++++++++++++++---------------------- Order.py | 27 ++++---- OrderSystem.py | 70 +++++++++---------- ProduceSystem.py | 75 ++++++++++++-------- demand23.xlsx | Bin 9870 -> 9591 bytes initial_material.xlsx | Bin 0 -> 11285 bytes initial_product.xlsx | Bin 0 -> 9563 bytes rawmaterial - s.xlsx | Bin 0 -> 11260 bytes rawmaterial.xlsx | Bin 10695 -> 0 bytes rawmaterialS.xlsx | Bin 0 -> 11256 bytes 15 files changed, 249 insertions(+), 191 deletions(-) create mode 100644 .idea/other.xml create mode 100644 initial_material.xlsx create mode 100644 initial_product.xlsx create mode 100644 rawmaterial - s.xlsx delete mode 100644 rawmaterial.xlsx create mode 100644 rawmaterialS.xlsx diff --git a/.idea/HTSim.iml b/.idea/HTSim.iml index d870a4a..7f92818 100644 --- a/.idea/HTSim.iml +++ b/.idea/HTSim.iml @@ -2,7 +2,10 @@ - + + + \ No newline at end of file diff --git a/.idea/misc.xml b/.idea/misc.xml index ab530bf..2479c47 100644 --- a/.idea/misc.xml +++ b/.idea/misc.xml @@ -1,4 +1,4 @@ - + \ No newline at end of file diff --git a/.idea/other.xml b/.idea/other.xml new file mode 100644 index 0000000..a708ec7 --- /dev/null +++ b/.idea/other.xml @@ -0,0 +1,6 @@ + + + + + \ No newline at end of file diff --git a/Environment.py b/Environment.py index 0ca7f73..cf6239a 100644 --- a/Environment.py +++ b/Environment.py @@ -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)) - return new_order - return None + # for i in range(xv_int_create_order_num): + new_order = Order(model=self, time_created=self.t) + return new_order + # 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]), diff --git a/Firm.py b/Firm.py index 22607b7..8a9e897 100644 --- a/Firm.py +++ b/Firm.py @@ -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() diff --git a/InventorySystem.py b/InventorySystem.py index e91548b..18ad354 100644 --- a/InventorySystem.py +++ b/InventorySystem.py @@ -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 # 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_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 - 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 + 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_material = xv_ary_initial_material_num # 115*2 + 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[ - 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 + 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 - diff --git a/Order.py b/Order.py index c6a8e89..3720ed5 100644 --- a/Order.py +++ b/Order.py @@ -6,30 +6,27 @@ 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 + ev_actual_dlv_t: int # 实际交付时间 - 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 - ev_actual_dlv_t: int # 实际交付时间 - - 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_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 # 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 diff --git a/OrderSystem.py b/OrderSystem.py index 004d0b6..99b7ff5 100644 --- a/OrderSystem.py +++ b/OrderSystem.py @@ -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_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 \ No newline at end of file diff --git a/ProduceSystem.py b/ProduceSystem.py index 63d25b7..7de0f74 100644 --- a/ProduceSystem.py +++ b/ProduceSystem.py @@ -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[ - 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]] + 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([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]) - break + 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]) - self.ev_ary_produce_number = np.array(self.ev_ary_produce_number) + break - return 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