修改100_100_6的dqn场景

Duel_Double_DQN/utils.py

@@ -47,7 +47,7 @@ def save_best_solution(info_lt):
 
     # 读取已有的最优解
     try:
-        with open('solutions/dqn_params_50_50_3.json', 'r') as f:
+        with open('solutions/dqn_params_100_100_6.json', 'r') as f:
             saved_solution = json.load(f)
             saved_time = saved_solution['best_time']
     except FileNotFoundError:
@@ -63,7 +63,7 @@ def save_best_solution(info_lt):
             'timestamp': datetime.now().strftime('%Y-%m-%d %H:%M:%S')
         }
 
-        with open('solutions/dqn_params_50_50_3.json', 'w') as f:
+        with open('solutions/dqn_params_100_100_6.json', 'w') as f:
             json.dump(best_solution, f, indent=4)
 
         print(f"发现新的最优解！时间: {best_info['best_time']}")

env_partion_dist.py

@@ -18,13 +18,13 @@ class PartitionEnv(gym.Env):
         ##############################
         # 可能需要手动修改的超参数
         ##############################
-        self.params = 'params_50_50_3'
+        self.params = 'params_100_100_6'
-        self.ORI_ROW_CUTS = [0, 0.2, 0.4, 0.7, 1]
+        self.ORI_ROW_CUTS = [0, 0.2, 0.5, 0.7, 1]
-        self.ORI_COL_CUTS = [0, 0.5, 1]
+        self.ORI_COL_CUTS = [0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1]
-        self.CUT_NUM = 4
+        self.CUT_NUM = 12
-        self.BASE_LINE = 9051.16
+        self.BASE_LINE = 19616.68
-        self.MAX_ADJUST_STEP = 50
+        self.MAX_ADJUST_STEP = 80
-        self.ADJUST_THRESHOLD = 0.1
+        # self.ADJUST_THRESHOLD = 0.1
         # self.mTSP_STEPS = 10000
 
         # 切分位置+/-0.01
@@ -73,26 +73,41 @@ class PartitionEnv(gym.Env):
         return state
 
     def step(self, action):
-        if action == 1:
+        # if action == 1:
-            self.row_cuts[1] += 0.01
+        #     self.row_cuts[1] += 0.01
-        elif action == 2:
+        # elif action == 2:
-            self.row_cuts[1] -= 0.01
+        #     self.row_cuts[1] -= 0.01
-        elif action == 3:
+        # elif action == 3:
-            self.row_cuts[2] += 0.01
+        #     self.row_cuts[2] += 0.01
-        elif action == 4:
+        # elif action == 4:
-            self.row_cuts[2] -= 0.01
+        #     self.row_cuts[2] -= 0.01
-        elif action == 5:
+        # elif action == 5:
-            self.row_cuts[3] += 0.01
+        #     self.row_cuts[3] += 0.01
-        elif action == 6:
+        # elif action == 6:
-            self.row_cuts[3] -= 0.01
+        #     self.row_cuts[3] -= 0.01
-        elif action == 7:
+        # elif action == 7:
-            self.col_cuts[1] += 0.01
+        #     self.col_cuts[1] += 0.01
-        elif action == 8:
+        # elif action == 8:
-            self.col_cuts[1] -= 0.01
+        #     self.col_cuts[1] -= 0.01
-        elif action == 0:
+        # elif action == 0:
+        #     pass
+        cut_index, signal = (action + 1) // 2, (action + 1) % 2
+        if action == 0:
             pass
+        elif cut_index <= 3:
+            if signal == 0:
+                self.row_cuts[cut_index] += 0.01
+            else:
+                self.row_cuts[cut_index] -= 0.01
+        else:
+            if signal == 0:
+                self.col_cuts[cut_index-3] += 0.01
+            else:
+                self.col_cuts[cut_index-3] -= 0.01
 
-        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]:
+        # 检查row_cuts和col_cuts是否按升序排列
+        if (all(self.row_cuts[i] < self.row_cuts[i+1] for i in range(len(self.row_cuts)-1)) and
+                all(self.col_cuts[i] < self.col_cuts[i+1] for i in range(len(self.col_cuts)-1))):
             # 调整是合法的，验证分区情况是否满足条件
             rectangles = self.if_valid_partition()
 
@@ -107,7 +122,8 @@ class PartitionEnv(gym.Env):
                 # 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]
+                self.best_path = [0, 17, 10, 9, 8, 7, 6, 5, 0, 28, 29, 30, 19, 20, 18, 16, 43, 27, 40, 39, 38, 37,
+                                  36, 26, 45, 14, 13, 12, 11, 22, 21, 23, 24, 41, 44, 25, 34, 35, 33, 32, 31, 42, 15, 4, 3, 2, 1, 0]
                 best_time = self.get_best_time(self.best_path, rectangles)
 
         else:
@@ -239,7 +255,7 @@ class PartitionEnv(gym.Env):
 
         # 使用tanh归一化，确保time_diff=0时，normalized_diff=0
         # tanh在变量值为2时，就非常接近1了。最大的time_diff为400
-        normalized_diff = np.tanh(time_diff / 200)  # 20是缩放因子，可调整
+        normalized_diff = np.tanh(time_diff / 5000)  # 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))

human_action.py

@@ -13,8 +13,7 @@ print('state:', state)
 # action_series = [1] * 30
 # action_series = [[0.2], [0.4], [0.7], [0.5]]
 # action_series = [[-0.08], [-0.08], [0], [0]]
-action_series = [3, 5, 3, 5, 1, 1, 3, 5, 1, 5, 3, 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1,
+action_series = [0, 0, 3, 4, 24, 20]
-                 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1]
 
 for i in range(100):
     action = action_series[i]

solutions/dqn_params_100_100_6.json

@@ -0,0 +1,74 @@
+{
+    "best_time": 19557.574055662244,
+    "row_cuts": [
+        0,
+        0.2,
+        0.5,
+        0.7,
+        1
+    ],
+    "col_cuts": [
+        0,
+        0.1,
+        0.19,
+        0.3,
+        0.4,
+        0.5,
+        0.6,
+        0.7,
+        0.8,
+        0.9,
+        1
+    ],
+    "best_path": [
+        0,
+        17,
+        10,
+        9,
+        8,
+        7,
+        6,
+        5,
+        0,
+        28,
+        29,
+        30,
+        19,
+        20,
+        18,
+        16,
+        43,
+        27,
+        40,
+        39,
+        38,
+        37,
+        36,
+        26,
+        45,
+        14,
+        13,
+        12,
+        11,
+        22,
+        21,
+        23,
+        24,
+        41,
+        25,
+        44,
+        34,
+        35,
+        33,
+        32,
+        31,
+        42,
+        15,
+        4,
+        3,
+        2,
+        1,
+        0
+    ],
+    "timestamp": "2025-04-04 10:47:47"
+}

solutions/trav_ga_params_100_100_6_parallel.json

@@ -1,5 +1,12 @@
 {
     "row_boundaries": [
+        0.0,
+        0.2,
+        0.5,
+        0.7,
+        1.0
+    ],
+    "col_boundaries": [
         0.0,
         0.1,
         0.2,
@@ -12,63 +19,58 @@
         0.9,
         1.0
     ],
-    "col_boundaries": [
-        0.0,
-        0.2,
-        0.4,
-        0.7,
-        1.0
-    ],
     "car_paths": [
         [
-            17,
+            16,
-            5,
-            4,
-            0,
-            1,
-            2,
-            6,
-            10,
-            14
-        ],
-        [
-            18,
-            13,
             9,
             8,
-            12,
-            16,
-            20,
-            32,
-            21
-        ],
-        [
-            22,
-            26,
-            30,
-            34,
-            39,
-            35,
-            31,
-            27,
-            19
-        ],
-        [
-            25,
-            24,
-            28,
-            36,
-            33,
-            37,
-            38,
-            29
-        ],
-        [
-            15,
-            23,
             7,
+            6,
+            5,
+            4
+        ],
+        [
+            27,
+            28,
+            29,
+            18,
+            19,
+            17,
+            15
+        ],
+        [
+            26,
+            39,
+            38,
+            37,
+            36,
+            35,
+            25
+        ],
+        [
+            13,
+            12,
             11,
-            3
+            10,
+            21,
+            20,
+            22,
+            23
+        ],
+        [
+            24,
+            33,
+            34,
+            32,
+            31,
+            30
+        ],
+        [
+            14,
+            3,
+            2,
+            1,
+            0
         ]
     ]
 }

visualization.py

@@ -200,7 +200,7 @@ if __name__ == "__main__":
     # 需要修改的超参数
     # ---------------------------
     params_file = 'params_100_100_6'
-    solution_file = r'solutions\greedy_params_100_100_6.json'
+    solution_file = r'solutions\trav_ga_params_100_100_6_parallel.json'
 
     with open(params_file + '.yml', 'r', encoding='utf-8') as file:
         params = yaml.safe_load(file)