W tej sekcji wyjaśniamy, jak rozwiązać problemy z wyznaczaniem tras, które nie są możliwe ze względu na ograniczenia. Na przykład, jeśli otrzymasz VRP z ograniczeniami pojemności w którym łączny popyt we wszystkich lokalizacjach przekracza łączne możliwości nie da się rozwiązać problemu. W takich przypadkach pojazdy muszą zrezygnować z wizyt w niektórych lokalizacjach. Problemem jest to, jak zdecydować, które wizyty warto usunąć.
Aby rozwiązać ten problem, wprowadzamy nowe koszty – tzw. kary we wszystkich lokalizacjach. Za każdym razem, gdy wizyta w danym miejscu zostaje usunięta, kara jest dodawana do całkowitej przebytej odległości. Rozwiązanie znajduje wtedy trasę, minimalizuje całkowitą odległość oraz sumę kar za wszystkie upadki lokalizacji.
Weźmy na przykład prostą VRP z ograniczeniami pojemności określonymi przez poniżej wykresu, gdzie liczby obok trzech lokalizacji (innych niż „depot”) to żądania.
Załóżmy, że jest tylko jeden pojazd o pojemności 50 miejsc. Nie może odwiedzić wszystkich trzech
lokalizacji, A, B i C, bo łączny popyt wynosi 60. Aby rozwiązać problem,
nakładasz na każdą lokalizację dużą karę, np. 100. Po
jeśli wykryje, że problem jest niemożliwy do wykonania, narzędzie pomija lokalizację B,
zwraca tę trasę: Depot -> A -> C -> Depot
Jest to najkrótsza trasa obejmująca dwie z trzech lokalizacji (czyli odległość wynosi 55).
Rozmiary kar
W przykładzie powyżej wybraliśmy kary wyższe niż suma wszystkich odległości między lokalizacjami (bez magazynu). W rezultacie po usunięciu do jednej lokalizacji, aby można było rozwiązać problem, lokalizacji, ponieważ kara za takie działanie przekroczyłaby i skrócenie czasu podróży.
Zakładając, że chcesz zrealizować jak najwięcej dostaw, satysfakcjonujące rozwiązanie problemu.
Jeśli nie musisz realizować tylu dostaw, możesz nałożenie mniejszych kar. W takim przypadku rozwiązanie może usunąć więcej lokalizacji niż jest konieczne do realizacji problemu. Możesz na przykład zrobić to, jeśli: oprócz podstawowych kosztów podróży obowiązują dodatkowe koszty, lokalizacji.
Przykład
W następnej kolejności przedstawiamy większy przykład VRP, który można rozwiązać za pomocą kar. Przykład jest podobny do poprzedniego CVRP, ale tym razem zwiększyliśmy przez co niektóre pojazdy rezygnują z wizyt.
Poniżej znajdziesz wykres przedstawiający lokalizacje i nowe zapotrzebowanie.
Rozwiąż przykład za pomocą narzędzi LUB
W sekcjach poniżej wyjaśniamy, jak rozwiązać ten przykład za pomocą narzędzi LUB.
Tworzenie danych
Dane w tym przykładzie obejmują dane z poprzedniego raportu przykładu korzystającego z VRP z uwzględnieniem tych żądań. i pojemności:
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 };
Dodaj ograniczenia i kary związane z wydajnością
Ten kod dodaje do żądania wywołania zwrotnego i ograniczenia pojemności oraz
kary oparte na
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); }
W tym kontekście rozróżnienie jest po prostu zmienną używaną przez rozwiązanie do uwzględnić daną lokalizację w rozwiązaniu. W tym przykładzie para klucz-wartość powoduje nałożenie takiej samej kary do każdej lokalizacji, ale generalnie możesz kary dla różnych lokalizacji.
Dodaj drukarkę rozwiązania
Drukarka rozwiązania widoczna poniżej jest podobna do CVRP, ale wyświetla też z porzuconych lokalizacji.
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); }
Przeprowadzanie programu
Po uruchomieniu programu zwraca on dane wyjściowe pokazane poniżej. Pamiętaj, że Rozwiązanie powoduje usunięcie lokalizacji 6 i 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
Oto schemat tras.
Kompletne programy
Oto pełne programy.
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); } }