Update google_solver/time_window_solver.py

google_solver/time_window_solver.py

@@ -1,4 +1,3 @@
-
 from __future__ import print_function
 from ortools.constraint_solver import routing_enums_pb2
 from ortools.constraint_solver import pywrapcp
@@ -6,63 +5,6 @@ from just_time_windows.dataloader import VRP_Dataset
 from just_time_windows.google_solver.convert_data import convert_data
 
 
-dataset = VRP_Dataset(dataset_size=1, num_nodes=20, num_depots=1)
-batch = dataset.get_batch(0, 1)
-
-data = convert_data(batch, scale_factor=100)
-data = data[0]
-
-
-def create_data_model():
-  """Stores the data for the problem."""
-  data = {}
-  data['time_matrix'] = [
-      [0, 6, 9, 8, 7, 3, 6, 2, 3, 2, 6, 6, 4, 4, 5, 9, 7],
-      [6, 0, 8, 3, 2, 6, 8, 4, 8, 8, 13, 7, 5, 8, 12, 10, 14],
-      [9, 8, 0, 11, 10, 6, 3, 9, 5, 8, 4, 15, 14, 13, 9, 18, 9],
-      [8, 3, 11, 0, 1, 7, 10, 6, 10, 10, 14, 6, 7, 9, 14, 6, 16],
-      [7, 2, 10, 1, 0, 6, 9, 4, 8, 9, 13, 4, 6, 8, 12, 8, 14],
-      [3, 6, 6, 7, 6, 0, 2, 3, 2, 2, 7, 9, 7, 7, 6, 12, 8],
-      [6, 8, 3, 10, 9, 2, 0, 6, 2, 5, 4, 12, 10, 10, 6, 15, 5],
-      [2, 4, 9, 6, 4, 3, 6, 0, 4, 4, 8, 5, 4, 3, 7, 8, 10],
-      [3, 8, 5, 10, 8, 2, 2, 4, 0, 3, 4, 9, 8, 7, 3, 13, 6],
-      [2, 8, 8, 10, 9, 2, 5, 4, 3, 0, 4, 6, 5, 4, 3, 9, 5],
-      [6, 13, 4, 14, 13, 7, 4, 8, 4, 4, 0, 10, 9, 8, 4, 13, 4],
-      [6, 7, 15, 6, 4, 9, 12, 5, 9, 6, 10, 0, 1, 3, 7, 3, 10],
-      [4, 5, 14, 7, 6, 7, 10, 4, 8, 5, 9, 1, 0, 2, 6, 4, 8],
-      [4, 8, 13, 9, 8, 7, 10, 3, 7, 4, 8, 3, 2, 0, 4, 5, 6],
-      [5, 12, 9, 14, 12, 6, 6, 7, 3, 3, 4, 7, 6, 4, 0, 9, 2],
-      [9, 10, 18, 6, 8, 12, 15, 8, 13, 9, 13, 3, 4, 5, 9, 0, 9],
-      [7, 14, 9, 16, 14, 8, 5, 10, 6, 5, 4, 10, 8, 6, 2, 9, 0],
-  ]
-
-
-  data['time_windows'] = [
-      (0, 0),  # depot
-      (7, 12),  # 1
-      (10, 15),  # 2
-      (16, 18),  # 3
-      (10, 13),  # 4
-      (0, 5),  # 5
-      (5, 10),  # 6
-      (0, 4),  # 7
-      (5, 10),  # 8
-      (0, 3),  # 9
-      (10, 16),  # 10
-      (10, 15),  # 11
-      (0, 5),  # 12
-      (5, 10),  # 13
-      (7, 8),  # 14
-      (10, 15),  # 15
-      (11, 15),  # 16
-  ]
-
-  data['num_vehicles'] = 4
-  data['depot'] = 0
-  return data
-
-
-
 def compute_total_time(data, routing, assignment):
     time_dimension = routing.GetDimensionOrDie('Time')
     total_time = 0
@@ -75,95 +17,86 @@ def compute_total_time(data, routing, assignment):
     return total_time
 
 
-
 def print_solution(data, manager, routing, assignment):
-    """Prints assignment on console."""
     time_dimension = routing.GetDimensionOrDie('Time')
     total_time = 0
     for vehicle_id in range(data['num_vehicles']):
         index = routing.Start(vehicle_id)
-        plan_output = 'Route for vehicle {}:\n'.format(vehicle_id)
+        plan_output = f'Route for vehicle {vehicle_id}:\n'
         while not routing.IsEnd(index):
             time_var = time_dimension.CumulVar(index)
-            plan_output += '{0} Time({1},{2}) -> '.format(
-                manager.IndexToNode(index), assignment.Min(time_var),
-                assignment.Max(time_var))
+            plan_output += f'{manager.IndexToNode(index)} Time({assignment.Min(time_var)},{assignment.Max(time_var)}) -> '
             index = assignment.Value(routing.NextVar(index))
         time_var = time_dimension.CumulVar(index)
-        plan_output += '{0} Time({1},{2})\n'.format(manager.IndexToNode(index),
-                                                    assignment.Min(time_var),
-                                                    assignment.Max(time_var))
-        plan_output += 'Time of the route: {}min\n'.format(
-            assignment.Min(time_var))
+        plan_output += f'{manager.IndexToNode(index)} Time({assignment.Min(time_var)},{assignment.Max(time_var)})\n'
+        plan_output += f'Time of the route: {assignment.Min(time_var)} min\n'
         print(plan_output)
         total_time += assignment.Min(time_var)
-    print('Total time of all routes: {}min'.format(total_time))
+    print(f'Total time of all routes: {total_time} min')
 
 
-def adjust_time_windows(D):
-    L = []
-    for x in D:
-        A = (x[0] + 10, x[1] + 10)
-        L.append(A)
-    return L
+def adjust_time_windows(windows, offset=10):
+    return [(start + offset, end + offset) for start, end in windows]
 
 
 def main():
-    """Solve the VRP with time windows."""
-
-    #data['time_windows'] = adjust_time_windows(data['time_windows'])
-
-    manager = pywrapcp.RoutingIndexManager(len(data['time_matrix']), data['num_vehicles'], data['depot'])
+    # إعداد مجموعة بيانات لاختبار نموذج time windows
+    dataset = VRP_Dataset(dataset_size=1, num_nodes=20, num_depots=1)
+    batch = dataset.get_batch(0, 1)
+    data = convert_data(batch, scale_factor=100)[0]
+
+    manager = pywrapcp.RoutingIndexManager(
+        len(data['time_matrix']),
+        data['num_vehicles'],
+        data['depot']
+    )
     routing = pywrapcp.RoutingModel(manager)
 
     def time_callback(from_index, to_index):
-        """Returns the travel time between the two nodes."""
-        # Convert from routing variable Index to time matrix NodeIndex.
         from_node = manager.IndexToNode(from_index)
         to_node = manager.IndexToNode(to_index)
         return data['time_matrix'][from_node][to_node]
 
     transit_callback_index = routing.RegisterTransitCallback(time_callback)
     routing.SetArcCostEvaluatorOfAllVehicles(transit_callback_index)
-    time = 'Time'
+
     routing.AddDimension(
         transit_callback_index,
-        10000,  # allow waiting time
-        10000,  # maximum time per vehicle
-        False,  # Don't force start cumul to zero.
-        time)
+        10000,
+        10000,
+        False,
+        'Time'
+    )
+
+    time_dimension = routing.GetDimensionOrDie('Time')
 
-    time_dimension = routing.GetDimensionOrDie(time)
-    # Add time window constraints for each location except depot.
+    # تعيين نوافذ زمنية للعقد
     for location_idx, time_window in enumerate(data['time_windows']):
-        if location_idx == 0:
-            continue
         index = manager.NodeToIndex(location_idx)
-        a, b = int(time_window[0]), int(time_window[1])
-        time_dimension.CumulVar(index).SetRange(a, b)
+        time_dimension.CumulVar(index).SetRange(int(time_window[0]), int(time_window[1]))
 
-    # Add time window constraints for each vehicle start node.
+    # تعيين نوافذ زمنية لنقاط بداية المركبات
     for vehicle_id in range(data['num_vehicles']):
         index = routing.Start(vehicle_id)
-
-        a, b = int(data['time_windows'][0][0]), int(data['time_windows'][0][1])
-        time_dimension.CumulVar(index).SetRange(a, b)
+        depot_window = data['time_windows'][0]
+        time_dimension.CumulVar(index).SetRange(int(depot_window[0]), int(depot_window[1]))
 
     for i in range(data['num_vehicles']):
-        routing.AddVariableMinimizedByFinalizer(
-            time_dimension.CumulVar(routing.Start(i)))
-        routing.AddVariableMinimizedByFinalizer(
-            time_dimension.CumulVar(routing.End(i)))
+        routing.AddVariableMinimizedByFinalizer(time_dimension.CumulVar(routing.Start(i)))
+        routing.AddVariableMinimizedByFinalizer(time_dimension.CumulVar(routing.End(i)))
 
     search_parameters = pywrapcp.DefaultRoutingSearchParameters()
-    search_parameters.first_solution_strategy = (
-        routing_enums_pb2.FirstSolutionStrategy.PATH_CHEAPEST_ARC)
+    search_parameters.first_solution_strategy = routing_enums_pb2.FirstSolutionStrategy.PATH_CHEAPEST_ARC
+
     assignment = routing.SolveWithParameters(search_parameters)
+
     if assignment:
         print_solution(data, manager, routing, assignment)
         total_time = compute_total_time(data, routing, assignment)
-        print(total_time)
+        print(f"\nFinal total time: {total_time} min")
+    else:
+        print("No solution found.")
 
 
 if __name__ == '__main__':
-  main()
+    main()