En esta sección, explicamos cómo abordar problemas de enrutamiento que no tienen una solución única debido a las limitaciones. Por ejemplo, si te dan un VRP con limitaciones de capacidad en las que la demanda total de todas las ubicaciones supera la capacidad total de vehículos, no hay solución posible. En esos casos, los vehículos deben disminuir las visitas a algunas ubicaciones. El problema es cómo decidir qué visitas abandonar.
Para resolver el problema, ingresamos nuevos costos, que se denominan penalizaciones. en todas las ubicaciones. Cuando se descarta una visita a una ubicación, la penalización se suma a la distancia total recorrida. Luego, el solucionador encuentra una ruta minimiza la distancia total más la suma de las penalizaciones para todas las pérdidas ubicaciones.
Como ejemplo, considera el VRP simple con limitaciones de capacidad proporcionadas por la gráfico a continuación, en el que los números junto a las tres ubicaciones (además de los depósito) son demandas.
Supongamos que hay un solo vehículo con capacidad de 50. No puede visitar los tres
A, B y C, porque la demanda total es de 60. Para resolver el problema,
asignas una penalización importante (por ejemplo, 100) a cada ubicación. Después del
detectar que el problema es inviable, el solucionador descarta la ubicación B y
devuelve la siguiente ruta: Depot -> A -> C -> Depot
Esta es la ruta más corta que visita dos de las tres ubicaciones (la distancia es de 55).
Tamaños de penalizaciones
En el ejemplo anterior, elegimos penalizaciones que son mayores que la suma de todos distancias entre ubicaciones (excepto el depósito). Como resultado, después de disminuir una ubicación para que el problema sea factible, la resolución no arroja ninguna ubicaciones adicionales porque la penalización superaría cualquier de reducción en la distancia de viaje.
Si quieren hacer tantas entregas como sea posible, una solución satisfactoria al problema.
Si no necesitas hacer tantas entregas como sea posible, asignar penalizaciones más pequeñas, en cuyo caso el solucionador puede disminuir la cantidad de ubicaciones que es necesaria para que el problema sea factible. Por ejemplo, podrías hacer esto si hay costos adicionales, por encima del costo básico de viaje, para visitar determinados ubicaciones.
Ejemplo
A continuación, presentamos un ejemplo más amplio de un VRP que se puede resolver mediante penalizaciones. El ejemplo es similar al anterior Ejemplo de CVRP, pero esta vez aumentamos algunas de las demandas, lo que obliga a algunos vehículos a disminuir las visitas.
A continuación, se muestra un gráfico de las ubicaciones y las nuevas demandas.
Resolver el ejemplo con las herramientas OR
Las siguientes secciones explican cómo resolver el ejemplo con las herramientas OR.
Crea los datos
Los datos de este ejemplo incluyen los datos del ejemplo Ejemplo de VRP y agrega las siguientes demandas y capacidades:
Python
data["demands"] = [0, 1, 1, 3, 6, 3, 6, 8, 8, 1, 2, 1, 2, 6, 6, 8, 8] data["vehicle_capacities"] = [15, 15, 15, 15]
C++
const std::vector<int64_t> demands{ 0, 1, 1, 3, 6, 3, 6, 8, 8, 1, 2, 1, 2, 6, 6, 8, 8, }; const std::vector<int64_t> vehicle_capacities{15, 15, 15, 15};
Java
public final long[] demands = {0, 1, 1, 3, 6, 3, 6, 8, 8, 1, 2, 1, 2, 6, 6, 8, 8}; public final long[] vehicleCapacities = {15, 15, 15, 15};
C#
public long[] Demands = { 0, 1, 1, 3, 6, 3, 6, 8, 8, 1, 2, 1, 2, 6, 6, 8, 8 }; public long[] VehicleCapacities = { 15, 15, 15, 15 };
Agrega las restricciones y penalizaciones de capacidad
El siguiente código agrega la devolución de llamada de demanda y las restricciones de capacidad, y agrega
penalizaciones con el
AddDisjunction
.
Python
def demand_callback(from_index): """Returns the demand of the node.""" # Convert from routing variable Index to demands NodeIndex. from_node = manager.IndexToNode(from_index) return data["demands"][from_node] demand_callback_index = routing.RegisterUnaryTransitCallback(demand_callback) routing.AddDimensionWithVehicleCapacity( demand_callback_index, 0, # null capacity slack data["vehicle_capacities"], # vehicle maximum capacities True, # start cumul to zero "Capacity", ) # Allow to drop nodes. penalty = 1000 for node in range(1, len(data["distance_matrix"])): routing.AddDisjunction([manager.NodeToIndex(node)], penalty)
C++
const int demand_callback_index = routing.RegisterUnaryTransitCallback( [&data, &manager](const int64_t from_index) -> int64_t { // Convert from routing variable Index to demand NodeIndex. const int from_node = manager.IndexToNode(from_index).value(); return data.demands[from_node]; }); routing.AddDimensionWithVehicleCapacity( demand_callback_index, // transit callback index int64_t{0}, // null capacity slack data.vehicle_capacities, // vehicle maximum capacities true, // start cumul to zero "Capacity"); // Allow to drop nodes. int64_t penalty{1000}; for (int i = 1; i < data.distance_matrix.size(); ++i) { routing.AddDisjunction( {manager.NodeToIndex(RoutingIndexManager::NodeIndex(i))}, penalty); }
Java
final int demandCallbackIndex = routing.registerUnaryTransitCallback((long fromIndex) -> { // Convert from routing variable Index to user NodeIndex. int fromNode = manager.indexToNode(fromIndex); return data.demands[fromNode]; }); routing.addDimensionWithVehicleCapacity(demandCallbackIndex, 0, // null capacity slack data.vehicleCapacities, // vehicle maximum capacities true, // start cumul to zero "Capacity"); // Allow to drop nodes. long penalty = 1000; for (int i = 1; i < data.distanceMatrix.length; ++i) { routing.addDisjunction(new long[] {manager.nodeToIndex(i)}, penalty); }
C#
int demandCallbackIndex = routing.RegisterUnaryTransitCallback((long fromIndex) => { // Convert from routing variable Index to // demand NodeIndex. var fromNode = manager.IndexToNode(fromIndex); return data.Demands[fromNode]; }); routing.AddDimensionWithVehicleCapacity(demandCallbackIndex, 0, // null capacity slack data.VehicleCapacities, // vehicle maximum capacities true, // start cumul to zero "Capacity"); // Allow to drop nodes. long penalty = 1000; for (int i = 1; i < data.DistanceMatrix.GetLength(0); ++i) { routing.AddDisjunction(new long[] { manager.NodeToIndex(i) }, penalty); }
En este contexto, una disyunción es simplemente una variable que usa la resolución para decidirán si incluir una ubicación dada en la solución. En este ejemplo, agrega la misma penalización a cada ubicación, pero, en general, puedes agregar y penalizaciones diferentes según la ubicación.
Agrega la impresora de la solución
La impresora de la solución, que se muestra a continuación, es similar a la de la ejemplo de CVRP, sino que también se muestra ubicaciones descartadas.
Python
def print_solution(data, manager, routing, assignment): """Prints assignment on console.""" print(f"Objective: {assignment.ObjectiveValue()}") # Display dropped nodes. dropped_nodes = "Dropped nodes:" for node in range(routing.Size()): if routing.IsStart(node) or routing.IsEnd(node): continue if assignment.Value(routing.NextVar(node)) == node: dropped_nodes += f" {manager.IndexToNode(node)}" print(dropped_nodes) # Display routes total_distance = 0 total_load = 0 for vehicle_id in range(data["num_vehicles"]): index = routing.Start(vehicle_id) plan_output = f"Route for vehicle {vehicle_id}:\n" route_distance = 0 route_load = 0 while not routing.IsEnd(index): node_index = manager.IndexToNode(index) route_load += data["demands"][node_index] plan_output += f" {node_index} Load({route_load}) -> " previous_index = index index = assignment.Value(routing.NextVar(index)) route_distance += routing.GetArcCostForVehicle( previous_index, index, vehicle_id ) plan_output += f" {manager.IndexToNode(index)} Load({route_load})\n" plan_output += f"Distance of the route: {route_distance}m\n" plan_output += f"Load of the route: {route_load}\n" print(plan_output) total_distance += route_distance total_load += route_load print(f"Total Distance of all routes: {total_distance}m") print(f"Total Load of all routes: {total_load}")
C++
//! @brief Print the solution. //! @param[in] data Data of the problem. //! @param[in] manager Index manager used. //! @param[in] routing Routing solver used. //! @param[in] solution Solution found by the solver. void PrintSolution(const DataModel& data, const RoutingIndexManager& manager, const RoutingModel& routing, const Assignment& solution) { // Display dropped nodes. std::ostringstream dropped_nodes; for (int64_t node = 0; node < routing.Size(); ++node) { if (routing.IsStart(node) || routing.IsEnd(node)) continue; if (solution.Value(routing.NextVar(node)) == node) { dropped_nodes << " " << manager.IndexToNode(node).value(); } } LOG(INFO) << "Dropped nodes:" << dropped_nodes.str(); // Display routes int64_t total_distance{0}; int64_t total_load{0}; for (int vehicle_id = 0; vehicle_id < data.num_vehicles; ++vehicle_id) { int64_t index = routing.Start(vehicle_id); LOG(INFO) << "Route for Vehicle " << vehicle_id << ":"; int64_t route_distance{0}; int64_t route_load{0}; std::ostringstream route; while (!routing.IsEnd(index)) { const int node_index = manager.IndexToNode(index).value(); route_load += data.demands[node_index]; route << node_index << " Load(" << route_load << ") -> "; const int64_t previous_index = index; index = solution.Value(routing.NextVar(index)); route_distance += routing.GetArcCostForVehicle(previous_index, index, int64_t{vehicle_id}); } LOG(INFO) << route.str() << manager.IndexToNode(index).value(); LOG(INFO) << "Distance of the route: " << route_distance << "m"; LOG(INFO) << "Load of the route: " << route_load; total_distance += route_distance; total_load += route_load; } LOG(INFO) << "Total distance of all routes: " << total_distance << "m"; LOG(INFO) << "Total load of all routes: " << total_load; LOG(INFO) << ""; LOG(INFO) << "Advanced usage:"; LOG(INFO) << "Problem solved in " << routing.solver()->wall_time() << "ms"; }
Java
/// @brief Print the solution. static void printSolution( DataModel data, RoutingModel routing, RoutingIndexManager manager, Assignment solution) { // Solution cost. logger.info("Objective: " + solution.objectiveValue()); // Inspect solution. // Display dropped nodes. String droppedNodes = "Dropped nodes:"; for (int node = 0; node < routing.size(); ++node) { if (routing.isStart(node) || routing.isEnd(node)) { continue; } if (solution.value(routing.nextVar(node)) == node) { droppedNodes += " " + manager.indexToNode(node); } } logger.info(droppedNodes); // Display routes long totalDistance = 0; long totalLoad = 0; for (int i = 0; i < data.vehicleNumber; ++i) { long index = routing.start(i); logger.info("Route for Vehicle " + i + ":"); long routeDistance = 0; long routeLoad = 0; String route = ""; while (!routing.isEnd(index)) { long nodeIndex = manager.indexToNode(index); routeLoad += data.demands[(int) nodeIndex]; route += nodeIndex + " Load(" + routeLoad + ") -> "; long previousIndex = index; index = solution.value(routing.nextVar(index)); routeDistance += routing.getArcCostForVehicle(previousIndex, index, i); } route += manager.indexToNode(routing.end(i)); logger.info(route); logger.info("Distance of the route: " + routeDistance + "m"); totalDistance += routeDistance; totalLoad += routeLoad; } logger.info("Total Distance of all routes: " + totalDistance + "m"); logger.info("Total Load of all routes: " + totalLoad); }
C#
/// <summary> /// Print the solution. /// </summary> static void PrintSolution(in DataModel data, in RoutingModel routing, in RoutingIndexManager manager, in Assignment solution) { Console.WriteLine($"Objective {solution.ObjectiveValue()}:"); // Inspect solution. // Display dropped nodes. string droppedNodes = "Dropped nodes:"; for (int index = 0; index < routing.Size(); ++index) { if (routing.IsStart(index) || routing.IsEnd(index)) { continue; } if (solution.Value(routing.NextVar(index)) == index) { droppedNodes += " " + manager.IndexToNode(index); } } Console.WriteLine("{0}", droppedNodes); // Inspect solution. long totalDistance = 0; long totalLoad = 0; for (int i = 0; i < data.VehicleNumber; ++i) { Console.WriteLine("Route for Vehicle {0}:", i); long routeDistance = 0; long routeLoad = 0; var index = routing.Start(i); while (routing.IsEnd(index) == false) { long nodeIndex = manager.IndexToNode(index); routeLoad += data.Demands[nodeIndex]; Console.Write("{0} Load({1}) -> ", nodeIndex, routeLoad); var previousIndex = index; index = solution.Value(routing.NextVar(index)); routeDistance += routing.GetArcCostForVehicle(previousIndex, index, 0); } Console.WriteLine("{0}", manager.IndexToNode((int)index)); Console.WriteLine("Distance of the route: {0}m", routeDistance); totalDistance += routeDistance; totalLoad += routeLoad; } Console.WriteLine("Total Distance of all routes: {0}m", totalDistance); Console.WriteLine("Total Load of all routes: {0}m", totalLoad); }
Cómo ejecutar el programa
Cuando ejecutas el programa, se muestra el siguiente resultado que se muestra a continuación. Ten en cuenta que la solución descarta las ubicaciones 6 y 15.
Objective: 7936 Dropped nodes: 6 15 Route for vehicle 0: 0 Load(0) -> 9 Load(1) -> 14 Load(7) -> 16 Load(15) -> 0 Load(15) Distance of the route: 1324m Load of the route: 15 Route for vehicle 1: 0 Load(0) -> 12 Load(2) -> 11 Load(3) -> 4 Load(9) -> 3 Load(12) -> 1 Load(13) -> 0 Load(13) Distance of the route: 1872m Load of the route: 13 Route for vehicle 2: 0 Load(0) -> 7 Load(8) -> 13 Load(14) -> 0 Load(14) Distance of the route: 868m Load of the route: 14 Route for vehicle 3: 0 Load(0) -> 8 Load(8) -> 10 Load(10) -> 2 Load(11) -> 5 Load(14) -> 0 Load(14) Distance of the route: 1872m Load of the route: 14 Total Distance of all routes: 5936m Total Load of all routes: 56
Este es un diagrama de las rutas.
Completar programas
Estos son los programas completos.
Python
"""Capacited Vehicles Routing Problem (CVRP).""" 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["demands"] = [0, 1, 1, 3, 6, 3, 6, 8, 8, 1, 2, 1, 2, 6, 6, 8, 8] data["vehicle_capacities"] = [15, 15, 15, 15] data["num_vehicles"] = 4 data["depot"] = 0 return data def print_solution(data, manager, routing, assignment): """Prints assignment on console.""" print(f"Objective: {assignment.ObjectiveValue()}") # Display dropped nodes. dropped_nodes = "Dropped nodes:" for node in range(routing.Size()): if routing.IsStart(node) or routing.IsEnd(node): continue if assignment.Value(routing.NextVar(node)) == node: dropped_nodes += f" {manager.IndexToNode(node)}" print(dropped_nodes) # Display routes total_distance = 0 total_load = 0 for vehicle_id in range(data["num_vehicles"]): index = routing.Start(vehicle_id) plan_output = f"Route for vehicle {vehicle_id}:\n" route_distance = 0 route_load = 0 while not routing.IsEnd(index): node_index = manager.IndexToNode(index) route_load += data["demands"][node_index] plan_output += f" {node_index} Load({route_load}) -> " previous_index = index index = assignment.Value(routing.NextVar(index)) route_distance += routing.GetArcCostForVehicle( previous_index, index, vehicle_id ) plan_output += f" {manager.IndexToNode(index)} Load({route_load})\n" plan_output += f"Distance of the route: {route_distance}m\n" plan_output += f"Load of the route: {route_load}\n" print(plan_output) total_distance += route_distance total_load += route_load print(f"Total Distance of all routes: {total_distance}m") print(f"Total Load of all routes: {total_load}") def main(): """Solve the CVRP problem.""" # Instantiate the data problem. data = create_data_model() # Create the routing index manager. 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 Capacity constraint. def demand_callback(from_index): """Returns the demand of the node.""" # Convert from routing variable Index to demands NodeIndex. from_node = manager.IndexToNode(from_index) return data["demands"][from_node] demand_callback_index = routing.RegisterUnaryTransitCallback(demand_callback) routing.AddDimensionWithVehicleCapacity( demand_callback_index, 0, # null capacity slack data["vehicle_capacities"], # vehicle maximum capacities True, # start cumul to zero "Capacity", ) # Allow to drop nodes. penalty = 1000 for node in range(1, len(data["distance_matrix"])): routing.AddDisjunction([manager.NodeToIndex(node)], penalty) # 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(1) # Solve the problem. assignment = routing.SolveWithParameters(search_parameters) # Print solution on console. if assignment: print_solution(data, manager, routing, assignment) if __name__ == "__main__": main()
C++
#include <cstdint> #include <sstream> #include <vector> #include "google/protobuf/duration.pb.h" #include "ortools/constraint_solver/routing.h" #include "ortools/constraint_solver/routing_enums.pb.h" #include "ortools/constraint_solver/routing_index_manager.h" #include "ortools/constraint_solver/routing_parameters.h" namespace operations_research { struct DataModel { const std::vector<std::vector<int64_t>> distance_matrix{ {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}, }; const std::vector<int64_t> demands{ 0, 1, 1, 3, 6, 3, 6, 8, 8, 1, 2, 1, 2, 6, 6, 8, 8, }; const std::vector<int64_t> vehicle_capacities{15, 15, 15, 15}; const int num_vehicles = 4; const RoutingIndexManager::NodeIndex depot{0}; }; //! @brief Print the solution. //! @param[in] data Data of the problem. //! @param[in] manager Index manager used. //! @param[in] routing Routing solver used. //! @param[in] solution Solution found by the solver. void PrintSolution(const DataModel& data, const RoutingIndexManager& manager, const RoutingModel& routing, const Assignment& solution) { // Display dropped nodes. std::ostringstream dropped_nodes; for (int64_t node = 0; node < routing.Size(); ++node) { if (routing.IsStart(node) || routing.IsEnd(node)) continue; if (solution.Value(routing.NextVar(node)) == node) { dropped_nodes << " " << manager.IndexToNode(node).value(); } } LOG(INFO) << "Dropped nodes:" << dropped_nodes.str(); // Display routes int64_t total_distance{0}; int64_t total_load{0}; for (int vehicle_id = 0; vehicle_id < data.num_vehicles; ++vehicle_id) { int64_t index = routing.Start(vehicle_id); LOG(INFO) << "Route for Vehicle " << vehicle_id << ":"; int64_t route_distance{0}; int64_t route_load{0}; std::ostringstream route; while (!routing.IsEnd(index)) { const int node_index = manager.IndexToNode(index).value(); route_load += data.demands[node_index]; route << node_index << " Load(" << route_load << ") -> "; const int64_t previous_index = index; index = solution.Value(routing.NextVar(index)); route_distance += routing.GetArcCostForVehicle(previous_index, index, int64_t{vehicle_id}); } LOG(INFO) << route.str() << manager.IndexToNode(index).value(); LOG(INFO) << "Distance of the route: " << route_distance << "m"; LOG(INFO) << "Load of the route: " << route_load; total_distance += route_distance; total_load += route_load; } LOG(INFO) << "Total distance of all routes: " << total_distance << "m"; LOG(INFO) << "Total load of all routes: " << total_load; LOG(INFO) << ""; LOG(INFO) << "Advanced usage:"; LOG(INFO) << "Problem solved in " << routing.solver()->wall_time() << "ms"; } void VrpDropNodes() { // Instantiate the data problem. DataModel data; // Create Routing Index Manager RoutingIndexManager manager(data.distance_matrix.size(), data.num_vehicles, data.depot); // Create Routing Model. RoutingModel routing(manager); // Create and register a transit callback. const int transit_callback_index = routing.RegisterTransitCallback( [&data, &manager](const int64_t from_index, const int64_t to_index) -> int64_t { // Convert from routing variable Index to distance matrix NodeIndex. const int from_node = manager.IndexToNode(from_index).value(); const int to_node = manager.IndexToNode(to_index).value(); return data.distance_matrix[from_node][to_node]; }); // Define cost of each arc. routing.SetArcCostEvaluatorOfAllVehicles(transit_callback_index); // Add Capacity constraint. const int demand_callback_index = routing.RegisterUnaryTransitCallback( [&data, &manager](const int64_t from_index) -> int64_t { // Convert from routing variable Index to demand NodeIndex. const int from_node = manager.IndexToNode(from_index).value(); return data.demands[from_node]; }); routing.AddDimensionWithVehicleCapacity( demand_callback_index, // transit callback index int64_t{0}, // null capacity slack data.vehicle_capacities, // vehicle maximum capacities true, // start cumul to zero "Capacity"); // Allow to drop nodes. int64_t penalty{1000}; for (int i = 1; i < data.distance_matrix.size(); ++i) { routing.AddDisjunction( {manager.NodeToIndex(RoutingIndexManager::NodeIndex(i))}, penalty); } // Setting first solution heuristic. RoutingSearchParameters search_parameters = DefaultRoutingSearchParameters(); search_parameters.set_first_solution_strategy( FirstSolutionStrategy::PATH_CHEAPEST_ARC); search_parameters.set_local_search_metaheuristic( LocalSearchMetaheuristic::GUIDED_LOCAL_SEARCH); search_parameters.mutable_time_limit()->set_seconds(1); // Solve the problem. const Assignment* solution = routing.SolveWithParameters(search_parameters); // Print solution on console. PrintSolution(data, manager, routing, *solution); } } // namespace operations_research int main(int /*argc*/, char* /*argv*/[]) { operations_research::VrpDropNodes(); return EXIT_SUCCESS; }
Java
package com.google.ortools.constraintsolver.samples; import com.google.ortools.Loader; import com.google.ortools.constraintsolver.Assignment; import com.google.ortools.constraintsolver.FirstSolutionStrategy; import com.google.ortools.constraintsolver.LocalSearchMetaheuristic; import com.google.ortools.constraintsolver.RoutingIndexManager; import com.google.ortools.constraintsolver.RoutingModel; import com.google.ortools.constraintsolver.RoutingSearchParameters; import com.google.ortools.constraintsolver.main; import com.google.protobuf.Duration; import java.util.logging.Logger; /** Minimal VRP.*/ public class VrpDropNodes { private static final Logger logger = Logger.getLogger(VrpDropNodes.class.getName()); static class DataModel { public final long[][] distanceMatrix = { {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}, }; public final long[] demands = {0, 1, 1, 3, 6, 3, 6, 8, 8, 1, 2, 1, 2, 6, 6, 8, 8}; public final long[] vehicleCapacities = {15, 15, 15, 15}; public final int vehicleNumber = 4; public final int depot = 0; } /// @brief Print the solution. static void printSolution( DataModel data, RoutingModel routing, RoutingIndexManager manager, Assignment solution) { // Solution cost. logger.info("Objective: " + solution.objectiveValue()); // Inspect solution. // Display dropped nodes. String droppedNodes = "Dropped nodes:"; for (int node = 0; node < routing.size(); ++node) { if (routing.isStart(node) || routing.isEnd(node)) { continue; } if (solution.value(routing.nextVar(node)) == node) { droppedNodes += " " + manager.indexToNode(node); } } logger.info(droppedNodes); // Display routes long totalDistance = 0; long totalLoad = 0; for (int i = 0; i < data.vehicleNumber; ++i) { long index = routing.start(i); logger.info("Route for Vehicle " + i + ":"); long routeDistance = 0; long routeLoad = 0; String route = ""; while (!routing.isEnd(index)) { long nodeIndex = manager.indexToNode(index); routeLoad += data.demands[(int) nodeIndex]; route += nodeIndex + " Load(" + routeLoad + ") -> "; long previousIndex = index; index = solution.value(routing.nextVar(index)); routeDistance += routing.getArcCostForVehicle(previousIndex, index, i); } route += manager.indexToNode(routing.end(i)); logger.info(route); logger.info("Distance of the route: " + routeDistance + "m"); totalDistance += routeDistance; totalLoad += routeLoad; } logger.info("Total Distance of all routes: " + totalDistance + "m"); logger.info("Total Load of all routes: " + totalLoad); } public static void main(String[] args) throws Exception { Loader.loadNativeLibraries(); // Instantiate the data problem. final DataModel data = new DataModel(); // Create Routing Index Manager RoutingIndexManager manager = new RoutingIndexManager(data.distanceMatrix.length, data.vehicleNumber, data.depot); // Create Routing Model. RoutingModel routing = new RoutingModel(manager); // Create and register a transit callback. final int transitCallbackIndex = routing.registerTransitCallback((long fromIndex, long toIndex) -> { // Convert from routing variable Index to user NodeIndex. int fromNode = manager.indexToNode(fromIndex); int toNode = manager.indexToNode(toIndex); return data.distanceMatrix[fromNode][toNode]; }); // Define cost of each arc. routing.setArcCostEvaluatorOfAllVehicles(transitCallbackIndex); // Add Capacity constraint. final int demandCallbackIndex = routing.registerUnaryTransitCallback((long fromIndex) -> { // Convert from routing variable Index to user NodeIndex. int fromNode = manager.indexToNode(fromIndex); return data.demands[fromNode]; }); routing.addDimensionWithVehicleCapacity(demandCallbackIndex, 0, // null capacity slack data.vehicleCapacities, // vehicle maximum capacities true, // start cumul to zero "Capacity"); // Allow to drop nodes. long penalty = 1000; for (int i = 1; i < data.distanceMatrix.length; ++i) { routing.addDisjunction(new long[] {manager.nodeToIndex(i)}, penalty); } // Setting first solution heuristic. RoutingSearchParameters searchParameters = main.defaultRoutingSearchParameters() .toBuilder() .setFirstSolutionStrategy(FirstSolutionStrategy.Value.PATH_CHEAPEST_ARC) .setLocalSearchMetaheuristic(LocalSearchMetaheuristic.Value.GUIDED_LOCAL_SEARCH) .setTimeLimit(Duration.newBuilder().setSeconds(1).build()) .build(); // Solve the problem. Assignment solution = routing.solveWithParameters(searchParameters); // Print solution on console. printSolution(data, routing, manager, solution); } }
C#
using System; using System.Collections.Generic; using Google.OrTools.ConstraintSolver; using Google.Protobuf.WellKnownTypes; // Duration /// <summary> /// Minimal Vrp with drop nodes. /// </summary> public class VrpDropNodes { class DataModel { public long[,] DistanceMatrix = { { 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 } }; public long[] Demands = { 0, 1, 1, 3, 6, 3, 6, 8, 8, 1, 2, 1, 2, 6, 6, 8, 8 }; public long[] VehicleCapacities = { 15, 15, 15, 15 }; public int VehicleNumber = 4; public int Depot = 0; }; /// <summary> /// Print the solution. /// </summary> static void PrintSolution(in DataModel data, in RoutingModel routing, in RoutingIndexManager manager, in Assignment solution) { Console.WriteLine($"Objective {solution.ObjectiveValue()}:"); // Inspect solution. // Display dropped nodes. string droppedNodes = "Dropped nodes:"; for (int index = 0; index < routing.Size(); ++index) { if (routing.IsStart(index) || routing.IsEnd(index)) { continue; } if (solution.Value(routing.NextVar(index)) == index) { droppedNodes += " " + manager.IndexToNode(index); } } Console.WriteLine("{0}", droppedNodes); // Inspect solution. long totalDistance = 0; long totalLoad = 0; for (int i = 0; i < data.VehicleNumber; ++i) { Console.WriteLine("Route for Vehicle {0}:", i); long routeDistance = 0; long routeLoad = 0; var index = routing.Start(i); while (routing.IsEnd(index) == false) { long nodeIndex = manager.IndexToNode(index); routeLoad += data.Demands[nodeIndex]; Console.Write("{0} Load({1}) -> ", nodeIndex, routeLoad); var previousIndex = index; index = solution.Value(routing.NextVar(index)); routeDistance += routing.GetArcCostForVehicle(previousIndex, index, 0); } Console.WriteLine("{0}", manager.IndexToNode((int)index)); Console.WriteLine("Distance of the route: {0}m", routeDistance); totalDistance += routeDistance; totalLoad += routeLoad; } Console.WriteLine("Total Distance of all routes: {0}m", totalDistance); Console.WriteLine("Total Load of all routes: {0}m", totalLoad); } public static void Main(String[] args) { // Instantiate the data problem. DataModel data = new DataModel(); // Create Routing Index Manager RoutingIndexManager manager = new RoutingIndexManager(data.DistanceMatrix.GetLength(0), data.VehicleNumber, data.Depot); // Create Routing Model. RoutingModel routing = new RoutingModel(manager); // Create and register a transit callback. int transitCallbackIndex = routing.RegisterTransitCallback((long fromIndex, long toIndex) => { // Convert from routing variable Index to // distance matrix NodeIndex. var fromNode = manager.IndexToNode(fromIndex); var toNode = manager.IndexToNode(toIndex); return data.DistanceMatrix[fromNode, toNode]; }); // Define cost of each arc. routing.SetArcCostEvaluatorOfAllVehicles(transitCallbackIndex); // Add Capacity constraint. int demandCallbackIndex = routing.RegisterUnaryTransitCallback((long fromIndex) => { // Convert from routing variable Index to // demand NodeIndex. var fromNode = manager.IndexToNode(fromIndex); return data.Demands[fromNode]; }); routing.AddDimensionWithVehicleCapacity(demandCallbackIndex, 0, // null capacity slack data.VehicleCapacities, // vehicle maximum capacities true, // start cumul to zero "Capacity"); // Allow to drop nodes. long penalty = 1000; for (int i = 1; i < data.DistanceMatrix.GetLength(0); ++i) { routing.AddDisjunction(new long[] { manager.NodeToIndex(i) }, penalty); } // Setting first solution heuristic. RoutingSearchParameters searchParameters = operations_research_constraint_solver.DefaultRoutingSearchParameters(); searchParameters.FirstSolutionStrategy = FirstSolutionStrategy.Types.Value.PathCheapestArc; searchParameters.LocalSearchMetaheuristic = LocalSearchMetaheuristic.Types.Value.GuidedLocalSearch; searchParameters.TimeLimit = new Duration { Seconds = 1 }; // Solve the problem. Assignment solution = routing.SolveWithParameters(searchParameters); // Print solution on console. PrintSolution(data, routing, manager, solution); } }