http://www.apache.org/licenses/LICENSE-2.0

%pip install ortools

import weakref

from ortools.constraint_solver import routing_enums_pb2
from ortools.constraint_solver import pywrapcp



def create_data_model():
    """Stores the data for the problem."""
    data = {}
    data["distance_matrix"] = [
        # fmt: off
      [0, 548, 776, 696, 582, 274, 502, 194, 308, 194, 536, 502, 388, 354, 468, 776, 662],
      [548, 0, 684, 308, 194, 502, 730, 354, 696, 742, 1084, 594, 480, 674, 1016, 868, 1210],
      [776, 684, 0, 992, 878, 502, 274, 810, 468, 742, 400, 1278, 1164, 1130, 788, 1552, 754],
      [696, 308, 992, 0, 114, 650, 878, 502, 844, 890, 1232, 514, 628, 822, 1164, 560, 1358],
      [582, 194, 878, 114, 0, 536, 764, 388, 730, 776, 1118, 400, 514, 708, 1050, 674, 1244],
      [274, 502, 502, 650, 536, 0, 228, 308, 194, 240, 582, 776, 662, 628, 514, 1050, 708],
      [502, 730, 274, 878, 764, 228, 0, 536, 194, 468, 354, 1004, 890, 856, 514, 1278, 480],
      [194, 354, 810, 502, 388, 308, 536, 0, 342, 388, 730, 468, 354, 320, 662, 742, 856],
      [308, 696, 468, 844, 730, 194, 194, 342, 0, 274, 388, 810, 696, 662, 320, 1084, 514],
      [194, 742, 742, 890, 776, 240, 468, 388, 274, 0, 342, 536, 422, 388, 274, 810, 468],
      [536, 1084, 400, 1232, 1118, 582, 354, 730, 388, 342, 0, 878, 764, 730, 388, 1152, 354],
      [502, 594, 1278, 514, 400, 776, 1004, 468, 810, 536, 878, 0, 114, 308, 650, 274, 844],
      [388, 480, 1164, 628, 514, 662, 890, 354, 696, 422, 764, 114, 0, 194, 536, 388, 730],
      [354, 674, 1130, 822, 708, 628, 856, 320, 662, 388, 730, 308, 194, 0, 342, 422, 536],
      [468, 1016, 788, 1164, 1050, 514, 514, 662, 320, 274, 388, 650, 536, 342, 0, 764, 194],
      [776, 868, 1552, 560, 674, 1050, 1278, 742, 1084, 810, 1152, 274, 388, 422, 764, 0, 798],
      [662, 1210, 754, 1358, 1244, 708, 480, 856, 514, 468, 354, 844, 730, 536, 194, 798, 0],
        # fmt: on
    ]
    data["num_vehicles"] = 4
    data["depot"] = 0
    return data


def print_solution(
    routing_manager: pywrapcp.RoutingIndexManager, routing_model: pywrapcp.RoutingModel
):
    """Prints solution on console."""
    print("################")
    print(f"Solution objective: {routing_model.CostVar().Value()}")
    total_distance = 0
    for vehicle_id in range(routing_manager.GetNumberOfVehicles()):
        index = routing_model.Start(vehicle_id)
        if routing_model.IsEnd(routing_model.NextVar(index).Value()):
            continue
        plan_output = f"Route for vehicle {vehicle_id}:\n"
        route_distance = 0
        while not routing_model.IsEnd(index):
            plan_output += f" {routing_manager.IndexToNode(index)} ->"
            previous_index = index
            index = routing_model.NextVar(index).Value()
            route_distance += routing_model.GetArcCostForVehicle(
                previous_index, index, vehicle_id
            )
        plan_output += f" {routing_manager.IndexToNode(index)}\n"
        plan_output += f"Distance of the route: {route_distance}m\n"
        print(plan_output)
        total_distance += route_distance
    print(f"Total Distance of all routes: {total_distance}m")



class SolutionCallback:
    """Create a solution callback."""

    def __init__(
        self,
        manager: pywrapcp.RoutingIndexManager,
        model: pywrapcp.RoutingModel,
        limit: int,
    ):
        # We need a weak ref on the routing model to avoid a cycle.
        self._routing_manager_ref = weakref.ref(manager)
        self._routing_model_ref = weakref.ref(model)
        self._counter = 0
        self._counter_limit = limit
        self.objectives = []

    def __call__(self):
        objective = int(
            self._routing_model_ref().CostVar().Value()
        )  # pytype: disable=attribute-error
        if not self.objectives or objective < self.objectives[-1]:
            self.objectives.append(objective)
            print_solution(self._routing_manager_ref(), self._routing_model_ref())
            self._counter += 1
        if self._counter > self._counter_limit:
            self._routing_model_ref().solver().FinishCurrentSearch()




def main():
    """Entry point of the program."""
    # Instantiate the data problem.
    data = create_data_model()

    # Create the routing index manager.
    routing_manager = pywrapcp.RoutingIndexManager(
        len(data["distance_matrix"]), data["num_vehicles"], data["depot"]
    )

    # Create Routing Model.
    routing_model = pywrapcp.RoutingModel(routing_manager)


    # Create and register a transit callback.
    def distance_callback(from_index, to_index):
        """Returns the distance between the two nodes."""
        # Convert from routing variable Index to distance matrix NodeIndex.
        from_node = routing_manager.IndexToNode(from_index)
        to_node = routing_manager.IndexToNode(to_index)
        return data["distance_matrix"][from_node][to_node]

    transit_callback_index = routing_model.RegisterTransitCallback(distance_callback)

    # Define cost of each arc.
    routing_model.SetArcCostEvaluatorOfAllVehicles(transit_callback_index)

    # Add Distance constraint.
    dimension_name = "Distance"
    routing_model.AddDimension(
        transit_callback_index,
        0,  # no slack
        3000,  # vehicle maximum travel distance
        True,  # start cumul to zero
        dimension_name,
    )
    distance_dimension = routing_model.GetDimensionOrDie(dimension_name)
    distance_dimension.SetGlobalSpanCostCoefficient(100)

    # Attach a solution callback.
    solution_callback = SolutionCallback(routing_manager, routing_model, 15)
    routing_model.AddAtSolutionCallback(solution_callback)

    # Setting first solution heuristic.
    search_parameters = pywrapcp.DefaultRoutingSearchParameters()
    search_parameters.first_solution_strategy = (
        routing_enums_pb2.FirstSolutionStrategy.PATH_CHEAPEST_ARC
    )
    search_parameters.local_search_metaheuristic = (
        routing_enums_pb2.LocalSearchMetaheuristic.GUIDED_LOCAL_SEARCH
    )
    search_parameters.time_limit.FromSeconds(5)

    # Solve the problem.
    solution = routing_model.SolveWithParameters(search_parameters)

    # Print solution on console.
    if solution:
        print(f"Best objective: {solution_callback.objectives[-1]}")
    else:
        print("No solution found !")


main()