用python写一个求解带时间窗的车辆路径问题的代码

好的，这里给您提供一个基于python的求解带时间窗的车辆路径问题的代码。代码使用了OR-Tools库中的vrp_time_windows示例，并在此基础上进行了修改。以下是代码：

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, 5, 4, 3, 6, 5, 4, 3],
        [5, 0, 3, 6, 7, 8, 5, 7],
        [4, 3, 0, 5, 4, 6, 7, 8],
        [3, 6, 5, 0, 3, 5, 6, 7],
        [6, 7, 4, 3, 0, 4, 7, 6],
        [5, 8, 6, 5, 4, 0, 3, 5],
        [4, 5, 7, 6, 7, 3, 0, 3],
        [3, 7, 8, 7, 6, 5, 3, 0]
    ]
    data['num_vehicles'] = 1
    data['depot'] = 0
    data['time_windows'] = [
        (0, 0),
        (75, 85),
        (75, 85),
        (45, 55),
        (0, 15),
        (60, 75),
        (0, 15),
        (45, 60)
    ]
    data['vehicle_capacities'] = [15]
    data['starts'] = [0]
    data['ends'] = [0]
    return data


def print_solution(data, manager, routing, solution):
    """Prints solution on console."""
    max_route_distance = 0
    for vehicle_id in range(data['num_vehicles']):
        index = routing.Start(vehicle_id)
        plan_output = 'Route for vehicle {}:\n'.format(vehicle_id)
        route_distance = 0
        while not routing.IsEnd(index):
            node_index = manager.IndexToNode(index)
            next_node_index = manager.IndexToNode(solution.Value(routing.NextVar(index)))
            route_distance += routing.GetArcCostForVehicle(node_index, next_node_index, vehicle_id)
            time_var = routing.GetDimensionOrDie(0).CumulVar(index)
            time_min = solution.Min(time_var)
            time_max = solution.Max(time_var)
            plan_output += '  {0} Time({1},{2}) -> '.format(node_index, time_min, time_max)
            index = solution.Value(routing.NextVar(index))
        node_index = manager.IndexToNode(index)
        time_var = routing.GetDimensionOrDie(0).CumulVar(index)
        time_min = solution.Min(time_var)
        time_max = solution.Max(time_var)
        plan_output += '  {0} Time({1},{2})\n'.format(node_index, time_min, time_max)
        plan_output += 'Distance of the route: {}m\n'.format(route_distance)
        print(plan_output)
        max_route_distance = max(route_distance, max_route_distance)
    print('Maximum distance of the routes: {}m'.format(max_route_distance))


def main():
    """Solve the VRP with time windows."""
    data = create_data_model()

    manager = pywrapcp.RoutingIndexManager(len(data['distance_matrix']),
                                           data['num_vehicles'], data['starts'], data['ends'])
    routing = pywrapcp.RoutingModel(manager)

    def distance_callback(from_index, to_index):
        """Returns the distance between the two nodes."""
        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)
    routing.SetArcCostEvaluatorOfAllVehicles(transit_callback_index)

    dimension_name = 'Time'
    routing.AddDimension(
        transit_callback_index,
        30,  # allow waiting time
        30,  # maximum time per vehicle
        False,  # Don't force start cumul to zero.
        dimension_name)
    time_dimension = routing.GetDimensionOrDie(dimension_name)

    for location_idx, time_window in enumerate(data['time_windows']):
        if location_idx == 0:
            continue
        index = manager.NodeToIndex(location_idx)
        time_dimension.CumulVar(index).SetRange(time_window[0], time_window[1])

    for vehicle_id in range(data['num_vehicles']):
        index = routing.Start(vehicle_id)
        time_dimension.CumulVar(index).SetRange(data['time_windows'][0][0], data['time_windows'][0][1])
        index = routing.End(vehicle_id)
        time_dimension.CumulVar(index).SetRange(data['time_windows'][0][0], data['time_windows'][0][1])

    for i in range(1, len(data['distance_matrix'])):
        routing.AddToAssignment(routing.VehicleVarIndex(i), 0)

    search_parameters = pywrapcp.DefaultRoutingSearchParameters()
    search_parameters.first_solution_strategy = (
        routing_enums_pb2.FirstSolutionStrategy.PATH_CHEAPEST_ARC)

    solution = routing.SolveWithParameters(search_parameters)
    if solution:
        print_solution(data, manager, routing, solution)


if __name__ == '__main__':
    main()

代码中的数据和代码结构可能与实际情况不符，需要根据实际需求进行修改。另外，需要安装OR-Tools库才能运行该代码，可以使用以下命令进行安装：

pip install ortools

希望能够对您有所帮助！