问Ortools VRP错误时，试图合并处罚和不同的起点-终点仓库

EN

    data['num_vehicles'] = 2
    data['start'] = [0, 4]
    data['end'] = [0, 4]

    data['num_vehicles'] = 2
    data['start'] = [0, 4]
    data['end'] = [0, 9]
    .........................
    #for node in range(1, len(data['penalties'])):
    #     routing.AddDisjunction([manager.NodeToIndex(node)], data['penalties'][node])

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'] = [
        [0, 2253, 2479, 2792, 4707, 6128, 1567, 5643, 1234, 3345, 1827], 
        [1731, 0, 2193, 2507, 3624, 5040, 3467, 2921, 5791, 1546, 2345], 
        [1867, 2112, 0, 676, 4406, 5824, 988, 4567, 2134, 4453, 2123], 
        [2339, 2585, 893, 0, 4879, 6302, 1543, 1298, 6890, 1456, 5623], 
        [4464, 3766, 5935, 4957, 0, 1749, 987, 3212, 3451, 5212, 3321], 
        [6568, 5862, 8023, 7055, 2148, 0, 4567, 2124, 4321, 3212, 1234],
        [731, 2193, 2507, 7624, 4040, 4467, 0, 2621, 3791, 1567, 1345],
        [1731, 3193, 1507, 3624, 6040, 2467, 4921, 0, 5791, 6723, 1345],
        [2731, 3193, 2507, 6204, 5040, 1467, 2210, 6791, 0, 2567, 6421],
        [3345, 1543, 4421, 1531, 5213, 3215, 1512, 6213, 2431, 0, 5673],
        [1832, 2421, 2144, 5232, 3214, 1234, 1432, 1231, 6321, 5461, 0],
        ]
    data['node_time'] = [0, 7200, 3600, 5400, 0, 5400, 7200, 3600, 7200, 0, 300]
    data['num_vehicles'] = 2
    data['start'] = [0, 4]
    data['end'] = [0, 9]
    # Penalizaciones por no visitar nodos (drop nodes) en caso de que no tenga solución:
    # MAXINT 0x7FFFFFFFFFFFFFF: Hace obligatoria la visita al nodo, no se puede eliminar de la solución
    # 1000000: Se puede no visitar el nodo con penalización. La penalización debe ser grande, mayor que 10x veces el mayor tiempo de visita, para evitar que salga mas rentable dejar caer el nodo que pagar la penalización
    # 0: En los nodos "depósito" de vehículos, no son visitas intermedias sino inicio y fin de la ruta.
    data['penalties'] = [0, 1000000, 1000000, 1000000, 0, 0x7FFFFFFFFFFFFFF, 0x7FFFFFFFFFFFFFF, 1000000, 1000000, 0, 1000000]
    return data


def print_solution(data, manager, routing, solution):
    """Prints solution on console."""
    print(f'Objective: {solution.ObjectiveValue()}')

    # Display dropped nodes.
    dropped_nodes = 'Nodos sin visitar:'
    for node in range(routing.Size()):
        if routing.IsStart(node) or routing.IsEnd(node):
            continue
        if solution.Value(routing.NextVar(node)) == node:
            dropped_nodes += ' {}'.format(manager.IndexToNode(node))
    print(dropped_nodes + '\n')

    max_route_distance = 0
    for vehicle_id in range(data['num_vehicles']):
        index = routing.Start(vehicle_id)
        plan_output = 'Ruta para vehículo {}:\n'.format(vehicle_id)
        route_distance = 0
        while not routing.IsEnd(index):
            plan_output += ' {} -> '.format(manager.IndexToNode(index))
            previous_index = index
            index = solution.Value(routing.NextVar(index))
            route_distance += routing.GetArcCostForVehicle(
                previous_index, index, vehicle_id)
        plan_output += '{}\n'.format(manager.IndexToNode(index))
        plan_output += 'Tiempo de la ruta: {}sg\n'.format(route_distance)
        print(plan_output)
        max_route_distance = max(route_distance, max_route_distance)
    print('Maximo tiempo de las rutas: {}sg'.format(max_route_distance))



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

    # Create the routing index manager.
    manager = pywrapcp.RoutingIndexManager(len(data['distance_matrix']),
                                           data['num_vehicles'], data['start'], data['end'])

    # Create Routing Model.
    routing = pywrapcp.RoutingModel(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 = manager.IndexToNode(from_index)
        to_node = manager.IndexToNode(to_index)
        tiempo_desplazamiento = data['distance_matrix'][from_node][to_node]
        tiempo_ejecucion = data['node_time'][to_node]
        return tiempo_desplazamiento + tiempo_ejecucion

    transit_callback_index = routing.RegisterTransitCallback(distance_callback)

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

    # Add Distance constraint.
    routing.AddDimension(
        transit_callback_index,
        0,  # no slack
        27000,  # vehicle maximum travel distance (7.5 hours, in seconds)
        True,  # start cumul to zero
        'Time')
    distance_dimension = routing.GetDimensionOrDie('Time')
    distance_dimension.SetGlobalSpanCostCoefficient(100)

    # Allow to drop nodes.
    for node in range(1, len(data['penalties'])):
        routing.AddDisjunction([manager.NodeToIndex(node)], data['penalties'][node])

    # 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.seconds = 30

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

    # Print solution on console.
    if solution:
        print_solution(data, manager, routing, solution)
    else:
        print('No solution found!')


if __name__ == '__main__':
    main()