OR-Tools VRP 使用距离维度设置每辆车的最大路线答案

【问题标题】：OR-Tools VRP set Maximum Route per Vehicle using Distance DimensionOR-Tools VRP 使用距离维度设置每辆车的最大路线
【发布时间】：2021-05-27 10:49:52
【问题描述】：

我在计算每辆车的路线距离时遇到问题

示例车辆数量：9
总地址：70

只返回 6 辆小汽车，其中一辆车申请了 36 条路线

目前，我使用的是距离维度，我也已经尝试过“计数器”维度，根据我们设置的最大路线，结果是正确的，但点之间的距离是随机的（示例结果：路线 1： 1KM，路线2：7KM，路线3：2KM）

我想设置每辆车的限制，但使用“距离”维度

我的代码

manager = pywrapcp.RoutingIndexManager(len(data['distance_matrix']),
                                           data['num_vehicles'], data['depot'])

    # 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)
        return data['distance_matrix'][from_node][to_node]


    transit_callback_index = routing.RegisterTransitCallback(distance_callback)

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

    # Add Distance constraint.
    dimension_name = 'Distance'
    routing.AddDimension(
        transit_callback_index,
        0,  # no slack
        100000,  # vehicle maximum travel distance
        True,  # start cumul to zero
        dimension_name)
    distance_dimension = routing.GetDimensionOrDie(dimension_name)
    distance_dimension.SetGlobalSpanCostCoefficient(100)

    # Setting first solution heuristic.
    search_parameters = pywrapcp.DefaultRoutingSearchParameters()
    search_parameters.first_solution_strategy = (
        routing_enums_pb2.FirstSolutionStrategy.PATH_CHEAPEST_ARC)

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

【问题讨论】：

标签： python or-tools

【解决方案1】：

创建维度时

routing.AddDimension(
        transit_callback_index,
        0,  # no slack
        100_000,  # vehicle maximum travel distance
        True,  # start cumul to zero
        dimension_name)

这里100_000 是硬上限。

要为每辆车设置特定限制，您可以使用超载方法 AddDimensionWithVehicleCapacity() 采用列表而不是容量值，即最大行驶距离。参考：https://github.com/google/or-tools/blob/b77bd3ac69b7f3bb02f55b7bab6cbb4bab3917f2/ortools/constraint_solver/routing.h#L448-L451
如果您想“平等地”分发节点，可以使用计数器：

  # Distribution
    routing.AddConstantDimension(
            1,
            manager.GetNumberOfNodes(),
            True, # start cumul to zero
            "Counter")
    counter_dimension = routing.GetDimensionOrDie("Counter")
    nb_visit = (manager.GetNumberOfNodes()) // manager.GetNumberOfVehicles()
    print(f'visit_mean: {nb_visit}')
    penalty = 10_000 # must be adapted to your problem
    for vehicle_id in range(data["num_vehicles"]):
      index = routing.End(vehicle_id)
      counter_dimension.SetCumulVarSoftLowerBound(index, nb_visit, penalty)
      counter_dimension.SetCumulVarSoftUpperBound(index, nb_visit + 1, penalty)

【讨论】：