update

.idea/.name

@@ -1 +1 @@
-OrderSystem.py
+Order.py

Environment.py

@@ -84,7 +84,7 @@ class FMSEnv(ap.Model):
             self.stop()
         else:
             print(f"running the {self.t} step")
-            print(self.the_firm.the_os.ev_ave_delay_time)
+            print("当期延误时长为：{}".format(self.the_firm.the_os.ev_ave_delay_time))
 
     # Record data after each simulation
     def update(self):  # ?
@@ -111,7 +111,7 @@ class FMSEnv(ap.Model):
 
 if __name__ == '__main__':
     dct_para = {
-        'time': 60,  # 进行总时间数
+        'time': 300,  # 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.

Order.py

@@ -21,7 +21,7 @@ class Order(ap.Agent):
     def setup(self, time_created):
         self.xv_time_created = time_created  # 订单创建时间
         # read the demand of 23 productions
-        self.xv_ary_dlv_product = np.asarray(pd.read_excel("demand23.xlsx").to_records(index=False))   # 接神经网络结果
+        self.xv_ary_dlv_product = np.asarray(tuple([tuple(x) for x in pd.read_excel("demand23.xlsx").values]))   # 接神经网络结果
         self.ev_ary_dlv_product = np.asarray(tuple(pd.read_excel("demand23.xlsx").iloc[:, 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  # 随机生成期望交付时间

OrderSystem.py

@@ -55,6 +55,7 @@ class OrderSystem(ap.Agent):
         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]
+        # print(gap_sorted)
         if gap_sorted[0] > 0:  # 判断是否存在库存不足
             pass
         else:
@@ -65,6 +66,7 @@ class OrderSystem(ap.Agent):
         sorted_indices = np.argsort(option[:, 3])[::-1]
         sorted_data = option[sorted_indices]
         self.ev_int_produce_type = sorted_data[0, 0]
+        # print(option)
         # return self.ev_int_produce_type
 
     def do_shipment(self, ev_ary_current_product):
@@ -76,8 +78,13 @@ class OrderSystem(ap.Agent):
         # Make shipments based on ranked order list
         self.ev_ave_delay_time = 0
         self.ev_changed_product = np.array([float(x) for x in ev_ary_current_product[:, 1]])  # 23x1 ndarray 存储本次库存的改变
+        # print(ev_ary_current_product)
+        print(self.a_lst_order[0].ev_ary_dlv_product)
+        if len(self.a_lst_order) > 1:
+            print(self.a_lst_order[1].ev_ary_dlv_product)
         for order in self.a_lst_order:
-            if order.xv_dlv_t == self.model.t:  # 第一次交付
+            # print(order.xv_dlv_t[0], self.model.t)
+            if order.xv_dlv_t[0] == self.model.t:  # 第一次交付
                 # Check and make shipment
                 order.ev_is_delivered = True
                 for i in range(self.xv_product_num):
@@ -86,7 +93,9 @@ class OrderSystem(ap.Agent):
                         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
+                if order.ev_is_delivered:
+                    print('hhh')
+            elif order.xv_dlv_t[0] < self.model.t and order.ev_is_delivered == False:  # 第二次交付
                 order.ev_is_delivered = True
                 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
@@ -98,7 +107,7 @@ class OrderSystem(ap.Agent):
                     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
+                    order.ev_int_delay_time = order.ev_actual_dlv_t - order.xv_dlv_t[0]
 
                     self.ev_ave_delay_time += order.ev_int_delay_time * delay_num / 10000