diff --git a/.idea/.gitignore b/.idea/.gitignore new file mode 100644 index 0000000..26d3352 --- /dev/null +++ b/.idea/.gitignore @@ -0,0 +1,3 @@ +# Default ignored files +/shelf/ +/workspace.xml diff --git a/.idea/.name b/.idea/.name new file mode 100644 index 0000000..fed8c48 --- /dev/null +++ b/.idea/.name @@ -0,0 +1 @@ +OrderSystem.py \ No newline at end of file diff --git a/.idea/HTSim.iml b/.idea/HTSim.iml new file mode 100644 index 0000000..d870a4a --- /dev/null +++ b/.idea/HTSim.iml @@ -0,0 +1,8 @@ + + + + + + + + \ No newline at end of file diff --git a/.idea/inspectionProfiles/profiles_settings.xml b/.idea/inspectionProfiles/profiles_settings.xml new file mode 100644 index 0000000..105ce2d --- /dev/null +++ b/.idea/inspectionProfiles/profiles_settings.xml @@ -0,0 +1,6 @@ + + + + \ No newline at end of file diff --git a/.idea/misc.xml b/.idea/misc.xml new file mode 100644 index 0000000..ab530bf --- /dev/null +++ b/.idea/misc.xml @@ -0,0 +1,4 @@ + + + + \ No newline at end of file diff --git a/.idea/modules.xml b/.idea/modules.xml new file mode 100644 index 0000000..6b96659 --- /dev/null +++ b/.idea/modules.xml @@ -0,0 +1,8 @@ + + + + + + + + \ No newline at end of file diff --git a/.idea/vcs.xml b/.idea/vcs.xml new file mode 100644 index 0000000..35eb1dd --- /dev/null +++ b/.idea/vcs.xml @@ -0,0 +1,6 @@ + + + + + + \ No newline at end of file diff --git a/ABMfim流程00.txt b/ABMfim流程00.txt new file mode 100644 index 0000000..4aa49c2 --- /dev/null +++ b/ABMfim流程00.txt @@ -0,0 +1,42 @@ +！按子系统功能！ + +Oss: +接收订单。 +计算到当期为止，未交付订单的各类产品与其库存之差，得到gap最大的产品，并将能获得该商品最大生产率的生产状态通知Iss和Pss。 + +交付当期到期和已经出现延期的订单，先进先出。 + +计算（env）延期平均时间：延期时间 * 延期产品数/10000 + +Iss： +按照Oss指定的生产状态，准备原材料并交付Pss（如果原材料不充足，就将能交付的先交付） + +每期末统计原材料使用情况，按照遗传算法提供的Sspolicy，选择是否订货（初始原材料备货为s），如果订货要随机生成该原材料的交货期。 + +每期末要更新原材料剩余情况（上一次余值+当期到货量-当期使用量） + +更新产成品期末库存。 + + +Pss： +根据Oss的指示，开始生产，如果原材料不充足，就按照gap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。 +（此处如果出现原材料余料，回交Iss） +生成最终生产结果，产成品交付Iss。 + + +！按流程 ！ + +Oss:接收订单。计算到当期为止，未交付订单的各类产品与其库存之差，得到gap最大的产品，并将能获得该商品最大生产率的生产状态通知Iss和Pss。 + +Iss：按照Oss指定的生产状态，准备原材料并交付Pss（如果原材料不充足，就将能交付的先交付）。 + +Pss：根据Oss的指示，开始生产，如果原材料不充足，就按照gap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。 +（此处如果出现原材料余料，回交Iss） +生成最终生产结果，产成品交付Iss。 + +Iss：统计原材料使用情况，按照遗传算法提供的Sspolicy，选择是否订货（初始原材料备货为s），如果订货要随机生成该原材料的交货期。 +每期末要更新原材料剩余情况（上一次余值+当期到货量-当期使用量）。 +更新产成品期末库存。 + +Oss：交付当期到期和已经出现延期的订单，先进先出。计算（env）延期平均时间：延期时间 * 延期产品数/10000 + diff --git a/Environment.py b/Environment.py new file mode 100644 index 0000000..0ca7f73 --- /dev/null +++ b/Environment.py @@ -0,0 +1,165 @@ +import random +import numpy as np +import pandas as pd +import agentpy as ap +from datetime import datetime +from numpy import random +import json + +from Firm import Firm +# import passive agents +from Order import Order + +from fake_api import get_plan_by_pp_id, get_bom_by_prd_id + + +class FMSEnv(ap.Model): + # put all parameters here, not in any other places + # xv_int_max_order: int + # ev_n_order_created: int + + the_firm: Firm + + # record data, define below + # op_os_n_total_order: int + # op_os_n_total_order_delayed: int + op_os_all_delay_time: list + # op_os_delay_ratio: float + # op_is_flt_material_room_left: float + # op_is_flt_product_room_left: float + + op_ps_str_status: str + op_os_to_dlv: np.ndarray + op_is_current_product: np.ndarray + op_is_current_material: np.ndarray + op_is_trans_material: np.ndarray + op_ps_back_trans_material: np.ndarray + op_ps_produced_num: np.ndarray + op_is_ip_mat_id: np.ndarray + op_ip_prd_s: np.ndarray + op_ip_prd_big_s: np.ndarray + op_ip_prd_est_pfm: int + + def __init__(self, dct_all_para, _run_id=None): + super().__init__() + + # create agents here + 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.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_int_dlv_period_lam = int(dct_all_para['xv_int_dlv_period_lam']) + # self.ev_n_order_created = 0 + + self.running = True + self.t = 0 + + # Creation of orders should be done in the environment + def create_order(self): + # Check if maximum number of orders has been reached + 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 + + # 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) + + self.the_firm.operating() + self.update() + + if self.t >= self.int_stop_time: + self.running = False + self.stop() + else: + print(f"running the {self.t} step") + + # Record data after each simulation + def update(self): + self.op_os_n_total_order = len(self.the_firm.the_os.a_lst_order) + # 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_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_is_current_product = self.model.the_firm.the_is.ev_ary_current_product + # + # self.op_is_current_material = self.model.the_firm.the_is.ev_ary_current_material + # + # self.op_is_trans_material= self.model.the_firm.the_is.ev_lst_trans_material + + 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 + + +if __name__ == '__main__': + dct_para = { + 'time': 60, + # '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. + # 'xv_int_dlv_period_lam': 8.5, + # 'xv_int_create_order_lam': 2, + # 'xv_ary_price_product': tuple([0.3,0.2,0.5,1]), + # '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_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_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]), + # "xv_ary_mat_material": tuple([0.0, 0.0]), + # "xv_flt_broken_rate": 0, + # "xv_flt_run_cost": 0.0, + # "name": "wait" + # }, + # "1": {"xv_flt_produce_rate": tuple([90.0, 0.0]), + # "xv_ary_mat_material": tuple([4.0, 1.0]), + # "xv_flt_broken_rate": 0.03, + # "xv_flt_run_cost": 40.0, + # "name": "produceA" + # }, + # "2": {"xv_flt_produce_rate": tuple([0.0, 60.0]), + # "xv_ary_mat_material": tuple([1.5, 5.0]), + # "xv_flt_broken_rate": 0.05, + # "xv_flt_run_cost": 50.0, + # "name": "produceB" + # }, + # "3": {"xv_flt_produce_rate": tuple([55.0, 30.0]), + # "xv_ary_mat_material": tuple([2.0, 1.5]), + # "xv_flt_broken_rate": 0.07, + # "xv_flt_run_cost": 60.0, + # "name": "produceAB" + # }, + # "-1": {"xv_flt_produce_rate": 0.0, + # "xv_ary_mat_material": tuple([0.0, 0.0]), + # "xv_flt_broken_rate": 0.1, + # "xv_flt_run_cost": 100.0, + # "name": "failed" + # } + # }) + + } + sample = ap.Sample(dct_para) + + exp = ap.Experiment(FMSEnv, sample, iterations=1, record=True) + results = exp.run() + # results['variables']['FMSEnv'].to_excel(f"simulation-results-{datetime.today().strftime('%Y-%m-%d-%H-%M-%S')}.xlsx", + # engine='openpyxl') diff --git a/Firm.py b/Firm.py new file mode 100644 index 0000000..22607b7 --- /dev/null +++ b/Firm.py @@ -0,0 +1,37 @@ +import numpy as np +import json + +from InventorySystem import InventorySystem +from OrderSystem import OrderSystem +from ProduceSystem import ProduceSystem + +# Create Company Instance +class Firm: + the_os: OrderSystem + the_is: InventorySystem + the_ps: ProduceSystem + + def __init__(self, env, dct_all_para): + 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']]) + + # create agents here + self.the_os = OrderSystem(env) + 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) + # self.the_fs = FinancialSystem(env, xv_flt_initial_cash=self.xv_flt_initial_cash) + + def operating(self): + self.the_os.rank_order() + self.the_ps.change_status() + self.the_ps.run_produce() + self.the_os.do_shipment() + # self.the_is.inventory_cost() + # self.the_fs.financial_calculating() diff --git a/InventorySystem.py b/InventorySystem.py new file mode 100644 index 0000000..a82daac --- /dev/null +++ b/InventorySystem.py @@ -0,0 +1,128 @@ +import agentpy as ap +import numpy as np +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 + 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 + + # 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_material_inventory: list + ev_lst_product_inventory: list + + # Material list + xv_lst_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 + + def setup(self, xv_ary_initial_material_num, + xv_ary_initial_product_num, xv_ary_lead_time): + + # 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, )) + + # 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() + # 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_lst_material_inventory = [] + self.ev_lst_product_inventory = [] + + self.xv_lst_material = pd.read_excel("rawmaterial.xlsx").to_numpy() + + self.xv_ary_bom = pd.read_excel("bom23.xlsx").to_numpy() + + 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,)) + + 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 + produce_plan = xv_plan_excel[xv_plan_excel[:, 0] == produce_state] + for 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 + + def material_check(self, ev_ary_material_state_to_use): + # 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] + + def consume_and_store(self, ev_ary_material_to_use, ev_ary_produced_num,ev_changed_product, + ev_lst_backtrans_material): + self.ev_lst_backtrans_quan_material = ev_lst_backtrans_material + # Update the inventory after production + for i in range(115): + 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] + 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 + + def material_replenishment(self): + # 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: + 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] + else: + self.ev_ary_num_material_to_order[i] = 0 + diff --git a/Order.py b/Order.py new file mode 100644 index 0000000..c6a8e89 --- /dev/null +++ b/Order.py @@ -0,0 +1,36 @@ +import agentpy as ap +import random +import numpy as np +from numpy import random +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 + + 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 + + xv_ary_dlv_product: np.ndarray + ev_ary_dlv_product: np.ndarray + + def setup(self, time_created): + self.xv_time_created = time_created + # 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_time_circle = np.random.randint(7, 11, 1) + self.xv_dlv_t = self.xv_time_created + self.xv_time_circle + self.ev_actual_dlv_t = self.xv_dlv_t + self.ev_int_delay_time = self.ev_actual_dlv_t - self.xv_dlv_t + + # Set the initial status of order to be undelivered, accepted + self.ev_is_delivered = False + self.ev_is_accepted = False diff --git a/OrderSystem.py b/OrderSystem.py new file mode 100644 index 0000000..004d0b6 --- /dev/null +++ b/OrderSystem.py @@ -0,0 +1,103 @@ +import agentpy as ap +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 + ev_changed_product: np.ndarray + # ev_ary_dlv_product: np.ndarray?????? + + def setup(self): + # 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.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 + + def accept_order(self, new_order): + # Determine whether the order is received and all are currently received + if new_order is not None: + new_order.ev_is_accepted = True + self.a_lst_order.append(new_order) + + def rank_order(self): + # Sort order + self.a_lst_order = self.a_lst_order.sort('xv_dlv_t', reverse=False) + + 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 += 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.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 + 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] + + 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] + self.ev_int_produce_type = sorted_data[0, 0] + return self.ev_int_produce_type + + 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 + 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)): + 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] + 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)): + 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_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 diff --git a/ProduceSystem.py b/ProduceSystem.py new file mode 100644 index 0000000..63d25b7 --- /dev/null +++ b/ProduceSystem.py @@ -0,0 +1,60 @@ +import agentpy as ap +import numpy as np +import random + + +class ProduceSystem(ap.Agent): + ev_str_status: str # 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 + self.ev_lst_backtrans_material = [] + + def change_status(self): + self.ev_str_status = self.model.the_firm.the_os.produce_status() + + + 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 + # 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] + sorted_data = ev_ary_product_to_produce[sorted_indices] # 对gap进行从大到小排序 + 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] + for material in product_material: + produce_number = min(produce_number, int( + self.ev_lst_backtrans_material[np.where(ev_lst_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]] + else: + for current_product in sorted_data_product: + product_material = xv_ary_bom[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[ + 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_ary_produce_number = np.array(self.ev_ary_produce_number) + + return self.ev_ary_produce_number, self.ev_lst_backtrans_material \ No newline at end of file diff --git a/bom23.csv b/bom23.csv new file mode 100644 index 0000000..bd0886b --- /dev/null +++ b/bom23.csv @@ -0,0 +1,208 @@ +prd_id,mtr_id,qty,unit +ADTB331M0611,Z013V09501055,0.000347,ƽ +ADTB331M0611,F00VC50A055,0.000418,ƽ +ADTB331M0611,SM26040B070,0.000033,ǧ +ADTB331M0611,D12073G2126b,0.0001, +ADTB331M0611,YG00002,9.33E-06, +ADTB331M0611,YHCP50A,0.00017,ǧ +ADTB331M0611,L063-109Y,0.0001,֧ +ADTB331M0611,P06-30I,0.0001,ֻ +ADTB331M0611,GT063T,0.000039,ǧ +AGTR4R7V0812,Z510V12001070,0.000623,ƽ +AGTR4R7V0812,F30VC20A070,0.000784,ƽ +AGTR4R7V0812,EHD450Z085,0.000094,ǧ +AGTR4R7V0812,D12087F2126,0.0001, 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0000000..b661fff Binary files /dev/null and b/demand23.xlsx differ diff --git a/fake_api.py b/fake_api.py new file mode 100644 index 0000000..341cf75 --- /dev/null +++ b/fake_api.py @@ -0,0 +1,20 @@ +import pandas as pd + +df_bom = pd.read_excel('bom23.xlsx', engine='openpyxl') + +df_plan = pd.read_excel('plan.xlsx', engine='openpyxl') + + +def get_bom_by_prd_id(prd_id): + df_sub = df_bom.loc[df_bom['prd_id'] == prd_id] + return df_sub[['mtr_id', 'qty']] + + +def get_plan_by_pp_id(pp_id): + df_sub = df_plan.loc[df_plan['pp_id'] == int(pp_id)] + return df_sub[['prd_id', 'size', 'rate']] + + +if __name__ == '__main__': + print(get_bom_by_prd_id('ADTB331M0611')) + print(get_plan_by_pp_id('0')) # 0, 6, 8, 10 diff --git a/plan.xlsx b/plan.xlsx new file mode 100644 index 0000000..2b9bb7c Binary files /dev/null and b/plan.xlsx differ diff --git a/rawmaterial.xlsx b/rawmaterial.xlsx new file mode 100644 index 0000000..fd5bbd1 Binary files /dev/null and b/rawmaterial.xlsx differ