修改dqn bug

GA/ga.py

@@ -16,7 +16,7 @@ class GA(object):
         self.location = data
         self.to_process_idx = to_process_idx
         self.rectangles = rectangles
-        self.epochs = 1500
+        self.epochs = 300
         self.ga_choose_ratio = 0.2
         self.mutate_ratio = 0.05
         # fruits中存每一个个体是下标的list
@@ -320,6 +320,7 @@ class GA(object):
             best_length = 1.0 / best_score
             # print(f"Epoch {i:3}: {best_length:.3f}")
         # print(1.0 / best_score)
+        # print(i)
         return tmp_best_one, 1.0 / best_score
 
 # if __name__ == '__main__':

GA/main.py

@@ -20,7 +20,7 @@ best_col_boundaries = None
 # ---------------------------
 R = 3
 C = 3
-params_file = 'params2'
+params_file = 'params_50_50_3'
 
 
 with open(params_file + '.yml', 'r', encoding='utf-8') as file:

env_partion_dist.py

@@ -89,7 +89,7 @@ class PartitionEnv(gym.Env):
             self.col_cuts[1] += 0.01
         elif action == 8:
             self.col_cuts[1] -= 0.01
-        elif action == 9:
+        elif action == 0:
             pass
 
         if self.row_cuts[0] < self.row_cuts[1] < self.row_cuts[2] < self.row_cuts[3] < self.row_cuts[4] and self.col_cuts[0] < self.col_cuts[1] < self.col_cuts[2]:
@@ -100,12 +100,14 @@ class PartitionEnv(gym.Env):
                 # 不满足条件，时间给一个很大的值
                 best_time = self.BASE_LINE * 2
             else:
-                # 满足条件，继续进行路径规划
-                # 每隔10步计算一次路径，第一次也需要计算路径，记录最佳路径
-                if self.adjust_step % 10 == 0 or self.adjust_step == 1 or self.best_path is None:
-                    best_time, self.best_path = self.ga_solver(rectangles)
-                else:
-                    # 根据最佳路径计算当前时间
+                # # 满足条件，继续进行路径规划
+                # # 每隔10步计算一次路径，第一次也需要计算路径，记录最佳路径
+                # if self.adjust_step % 10 == 0 or self.adjust_step == 1 or self.best_path is None:
+                #     best_time, self.best_path = self.ga_solver(rectangles)
+                # else:
+                #     # 根据最佳路径计算当前时间
+                #     best_time = self.get_best_time(self.best_path, rectangles)
+                self.best_path = [0, 1, 3, 5, 9, 7, 8, 10, 2, 4, 6, 0]
                 best_time = self.get_best_time(self.best_path, rectangles)
 
         else:
@@ -240,10 +242,11 @@ class PartitionEnv(gym.Env):
         normalized_diff = np.tanh(time_diff / 200)  # 20是缩放因子，可调整
 
         # 计算轮次权重（折扣因子）
-        step_weight = 1 / (1 + np.exp(-self.adjust_step/10))
+        # step_weight = 1 / (1 + np.exp(-self.adjust_step/10))
 
         # 计算最终奖励
-        reward = normalized_diff * step_weight  # 10是缩放因子
+        reward = normalized_diff 
+        # * step_weight  # 10是缩放因子
 
         return reward
 

human_action.py

@@ -9,8 +9,8 @@ state = env.reset()
 print('state:', state)
 
 # action_series = [[0.67], [0], [0], [0], [0.7]]
-action_series = [1, 1, 1, 1, 1, 1]
-action_series = [1] * 30
+action_series = [3, 3, 3, 5, 5, 1, 1, 1, 0, 0, 0]
+# action_series = [1] * 30
 # action_series = [[0.2], [0.4], [0.7], [0.5]]
 # action_series = [[-0.08], [-0.08], [0], [0]]
 

solutions/dqn_params_50_50_3.json

@@ -1,10 +1,10 @@
 {
-    "best_time": 9051.162633521315,
+    "best_time": 8848.626166217664,
     "row_cuts": [
         0,
-        0.21000000000000002,
-        0.4,
-        0.7,
+        0.2700000000000001,
+        0.4700000000000001,
+        0.76,
         1
     ],
     "col_cuts": [
@@ -13,17 +13,18 @@
         1
     ],
     "best_path": [
+        0,
+        1,
+        3,
+        5,
+        9,
         7,
         8,
-        0,
-        6,
+        10,
         2,
         4,
-        10,
-        9,
-        5,
-        3,
-        1
+        6,
+        0
     ],
-    "timestamp": "2025-04-01 17:43:22"
+    "timestamp": "2025-04-01 20:05:51"
 }

visualization.py

@@ -200,7 +200,7 @@ if __name__ == "__main__":
     # 需要修改的超参数
     # ---------------------------
     params_file = 'params_50_50_3'
-    solution_file = r'solutions\trav_ga_params_50_50_3_parallel.json'
+    solution_file = r'solutions\finetune_params_50_50_3.json'
 
     with open(params_file + '.yml', 'r', encoding='utf-8') as file:
         params = yaml.safe_load(file)