इस सेक्शन में हमने एक ऐसे वीआरपी के बारे में बताया है जिसमें हर वाहन किसी आइटम को पिक अप करता है और उन्हें अलग-अलग जगहों पर छोड़ देता है. समस्या रूट असाइन करने की है इससे वाहनों को सभी आइटम को पिक अप और डिलीवर करने में मदद मिलेगी. साथ ही, सबसे लंबे रास्ते की लंबाई.
पिकअप और डिलीवरी के साथ VRP का उदाहरण
नीचे दिए गए डायग्राम में, मिलते-जुलते ग्रिड के लिए पिकअप और डिलीवरी की जगहों की जानकारी दिखाई गई है वीआरपी के पिछले उदाहरण में बताया गया है. हर एक के लिए आइटम, पिकअप स्थान से डिलीवरी स्थान तक एक निर्देशित किनारे है.
OR-टूल की मदद से उदाहरण हल करना
नीचे दिए गए सेक्शन में बताया गया है कि पिकअप और डिलीवरी के साथ वीआरपी की समस्या कैसे हल की जाए को अपनाएं. कोड का बड़ा हिस्सा इस रिपोर्ट से लिया गया है पिछले VRP उदाहरण को ध्यान में रखते हुए, हम उन चीज़ों पर फ़ोकस करें जो नए हैं.
डेटा बनाना
सवाल से जुड़े डेटा में, पिछले वीआरपी के हिसाब से दूरी का मैट्रिक्स शामिल है
उदाहरण के लिए, पिकअप और डिलीवरी की जगहों की लिस्ट दी गई होगी.
data['pickups_deliveries']
, डायग्राम में बताए गए किनारों के हिसाब से है
पढ़ें. नीचे दिया गया कोड, पिक अप और डिलीवरी की जगहों के बारे में बताता है.
Python
data["pickups_deliveries"] = [ [1, 6], [2, 10], [4, 3], [5, 9], [7, 8], [15, 11], [13, 12], [16, 14], ]
C++
const std::vector<std::vector<RoutingIndexManager::NodeIndex>> pickups_deliveries{ {RoutingIndexManager::NodeIndex{1}, RoutingIndexManager::NodeIndex{6}}, {RoutingIndexManager::NodeIndex{2}, RoutingIndexManager::NodeIndex{10}}, {RoutingIndexManager::NodeIndex{4}, RoutingIndexManager::NodeIndex{3}}, {RoutingIndexManager::NodeIndex{5}, RoutingIndexManager::NodeIndex{9}}, {RoutingIndexManager::NodeIndex{7}, RoutingIndexManager::NodeIndex{8}}, {RoutingIndexManager::NodeIndex{15}, RoutingIndexManager::NodeIndex{11}}, {RoutingIndexManager::NodeIndex{13}, RoutingIndexManager::NodeIndex{12}}, {RoutingIndexManager::NodeIndex{16}, RoutingIndexManager::NodeIndex{14}}, };
Java
public final int[][] pickupsDeliveries = { {1, 6}, {2, 10}, {4, 3}, {5, 9}, {7, 8}, {15, 11}, {13, 12}, {16, 14}, };
C#
public int[][] PickupsDeliveries = { new int[] { 1, 6 }, new int[] { 2, 10 }, new int[] { 4, 3 }, new int[] { 5, 9 }, new int[] { 7, 8 }, new int[] { 15, 11 }, new int[] { 13, 12 }, new int[] { 16, 14 }, };
हर जोड़े के लिए, पहली एंट्री में पिकअप की जगह का इंडेक्स होता है. इसके बाद, दूसरी एंट्री में डिलीवरी की जगह का इंडेक्स है.
पिकअप और डिलीवरी के अनुरोध तय करें
नीचे दिया गया कोड, पिकअप और डिलीवरी के अनुरोधों के बारे में बताता है.
data['pickups_deliveries']
में डिलीवरी की जगह.
Python
for request in data["pickups_deliveries"]: pickup_index = manager.NodeToIndex(request[0]) delivery_index = manager.NodeToIndex(request[1]) routing.AddPickupAndDelivery(pickup_index, delivery_index) routing.solver().Add( routing.VehicleVar(pickup_index) == routing.VehicleVar(delivery_index) ) routing.solver().Add( distance_dimension.CumulVar(pickup_index) <= distance_dimension.CumulVar(delivery_index) )
C++
Solver* const solver = routing.solver(); for (const auto& request : data.pickups_deliveries) { const int64_t pickup_index = manager.NodeToIndex(request[0]); const int64_t delivery_index = manager.NodeToIndex(request[1]); routing.AddPickupAndDelivery(pickup_index, delivery_index); solver->AddConstraint(solver->MakeEquality( routing.VehicleVar(pickup_index), routing.VehicleVar(delivery_index))); solver->AddConstraint( solver->MakeLessOrEqual(distance_dimension->CumulVar(pickup_index), distance_dimension->CumulVar(delivery_index))); }
Java
Solver solver = routing.solver(); for (int[] request : data.pickupsDeliveries) { long pickupIndex = manager.nodeToIndex(request[0]); long deliveryIndex = manager.nodeToIndex(request[1]); routing.addPickupAndDelivery(pickupIndex, deliveryIndex); solver.addConstraint( solver.makeEquality(routing.vehicleVar(pickupIndex), routing.vehicleVar(deliveryIndex))); solver.addConstraint(solver.makeLessOrEqual( distanceDimension.cumulVar(pickupIndex), distanceDimension.cumulVar(deliveryIndex))); }
C#
Solver solver = routing.solver(); for (int i = 0; i < data.PickupsDeliveries.GetLength(0); i++) { long pickupIndex = manager.NodeToIndex(data.PickupsDeliveries[i][0]); long deliveryIndex = manager.NodeToIndex(data.PickupsDeliveries[i][1]); routing.AddPickupAndDelivery(pickupIndex, deliveryIndex); solver.Add(solver.MakeEquality(routing.VehicleVar(pickupIndex), routing.VehicleVar(deliveryIndex))); solver.Add(solver.MakeLessOrEqual(distanceDimension.CumulVar(pickupIndex), distanceDimension.CumulVar(deliveryIndex))); }
हर जोड़ी के लिए,
routing.AddPickupAndDelivery(pickup_index, delivery_index)
, पिक अप के लिए बुकिंग कर रहा है
और किसी आइटम की डिलीवरी का अनुरोध करते हैं.
नीचे दी गई लाइन में, यह ज़रूरी शर्त जोड़ी गई है कि हर सामान को पिक अप करें और जिसे उसी वाहन से डिलीवर किया गया हो.
routing.solver().Add( routing.VehicleVar(pickup_index) == routing.VehicleVar(delivery_index))
आखिर में, हम एक ज़रूरी शर्त जोड़ते हैं कि हर सामान को पिक अप किया जाना ज़रूरी है डिलीवर करने से पहले. ऐसा करने के लिए, हम चाहते हैं कि किसी सामान को पिकअप करने की जगह पर वाहन की कुल दूरी डिलीवरी की जगह तक पहुंचने के बाद, उसकी कुल दूरी तय नहीं की जा सकती.
routing.solver().Add( distance_dimension.CumulVar(pickup_index) <= distance_dimension.CumulVar(delivery_index))
प्रोग्राम को चलाने का तरीका
पिकअप और डिलीवरी के साथ VRP के लिए पूरे प्रोग्राम इसमें दिखाए गए हैं अगला सेक्शन देखें. प्रोग्राम को चलाने पर, यह नीचे दिए गए रूट दिखाता है.
Objective: 226116 Route for vehicle 0: 0 -> 13 -> 15 -> 11 -> 12 -> 0 Distance of the route: 1552m Route for vehicle 1: 0 -> 5 -> 2 -> 10 -> 16 -> 14 -> 9 -> 0 Distance of the route: 2192m Route for vehicle 2: 0 -> 4 -> 3 -> 0 Distance of the route: 1392m Route for vehicle 3: 0 -> 7 -> 1 -> 6 -> 8 -> 0 Distance of the route: 1780m Total Distance of all routes: 6916m
नीचे दिए गए डायग्राम में रूट दिखाया गया है:
प्रोग्राम पूरे करें
सभी प्रोग्राम नीचे दिखाए गए हैं.
Python
"""Simple Pickup Delivery Problem (PDP).""" 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["pickups_deliveries"] = [ [1, 6], [2, 10], [4, 3], [5, 9], [7, 8], [15, 11], [13, 12], [16, 14], ] data["num_vehicles"] = 4 data["depot"] = 0 return data def print_solution(data, manager, routing, solution): """Prints solution on console.""" print(f"Objective: {solution.ObjectiveValue()}") total_distance = 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 while not routing.IsEnd(index): plan_output += f" {manager.IndexToNode(index)} -> " previous_index = index index = solution.Value(routing.NextVar(index)) route_distance += routing.GetArcCostForVehicle( previous_index, index, vehicle_id ) plan_output += f"{manager.IndexToNode(index)}\n" plan_output += f"Distance of the route: {route_distance}m\n" print(plan_output) total_distance += route_distance print(f"Total Distance of all routes: {total_distance}m") 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["depot"] ) # Create Routing Model. routing = pywrapcp.RoutingModel(manager) # Define cost of each arc. def distance_callback(from_index, to_index): """Returns the manhattan 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) routing.SetArcCostEvaluatorOfAllVehicles(transit_callback_index) # Add Distance constraint. dimension_name = "Distance" routing.AddDimension( transit_callback_index, 0, # no slack 3000, # vehicle maximum travel distance True, # start cumul to zero dimension_name, ) distance_dimension = routing.GetDimensionOrDie(dimension_name) distance_dimension.SetGlobalSpanCostCoefficient(100) # Define Transportation Requests. for request in data["pickups_deliveries"]: pickup_index = manager.NodeToIndex(request[0]) delivery_index = manager.NodeToIndex(request[1]) routing.AddPickupAndDelivery(pickup_index, delivery_index) routing.solver().Add( routing.VehicleVar(pickup_index) == routing.VehicleVar(delivery_index) ) routing.solver().Add( distance_dimension.CumulVar(pickup_index) <= distance_dimension.CumulVar(delivery_index) ) # Setting first solution heuristic. search_parameters = pywrapcp.DefaultRoutingSearchParameters() search_parameters.first_solution_strategy = ( routing_enums_pb2.FirstSolutionStrategy.PARALLEL_CHEAPEST_INSERTION ) # Solve the problem. solution = routing.SolveWithParameters(search_parameters) # Print solution on console. if solution: print_solution(data, manager, routing, solution) if __name__ == "__main__": main()
C++
#include <cstdint> #include <sstream> #include <vector> #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<std::vector<RoutingIndexManager::NodeIndex>> pickups_deliveries{ {RoutingIndexManager::NodeIndex{1}, RoutingIndexManager::NodeIndex{6}}, {RoutingIndexManager::NodeIndex{2}, RoutingIndexManager::NodeIndex{10}}, {RoutingIndexManager::NodeIndex{4}, RoutingIndexManager::NodeIndex{3}}, {RoutingIndexManager::NodeIndex{5}, RoutingIndexManager::NodeIndex{9}}, {RoutingIndexManager::NodeIndex{7}, RoutingIndexManager::NodeIndex{8}}, {RoutingIndexManager::NodeIndex{15}, RoutingIndexManager::NodeIndex{11}}, {RoutingIndexManager::NodeIndex{13}, RoutingIndexManager::NodeIndex{12}}, {RoutingIndexManager::NodeIndex{16}, RoutingIndexManager::NodeIndex{14}}, }; 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) { int64_t total_distance{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}; std::stringstream route; while (!routing.IsEnd(index)) { route << manager.IndexToNode(index).value() << " -> "; 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"; total_distance += route_distance; } LOG(INFO) << "Total distance of all routes: " << total_distance << "m"; LOG(INFO) << ""; LOG(INFO) << "Advanced usage:"; LOG(INFO) << "Problem solved in " << routing.solver()->wall_time() << "ms"; } void VrpGlobalSpan() { // 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); // Define cost of each arc. 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]; }); routing.SetArcCostEvaluatorOfAllVehicles(transit_callback_index); // Add Distance constraint. routing.AddDimension(transit_callback_index, // transit callback 0, // no slack 3000, // vehicle maximum travel distance true, // start cumul to zero "Distance"); RoutingDimension* distance_dimension = routing.GetMutableDimension("Distance"); distance_dimension->SetGlobalSpanCostCoefficient(100); // Define Transportation Requests. Solver* const solver = routing.solver(); for (const auto& request : data.pickups_deliveries) { const int64_t pickup_index = manager.NodeToIndex(request[0]); const int64_t delivery_index = manager.NodeToIndex(request[1]); routing.AddPickupAndDelivery(pickup_index, delivery_index); solver->AddConstraint(solver->MakeEquality( routing.VehicleVar(pickup_index), routing.VehicleVar(delivery_index))); solver->AddConstraint( solver->MakeLessOrEqual(distance_dimension->CumulVar(pickup_index), distance_dimension->CumulVar(delivery_index))); } // Setting first solution heuristic. RoutingSearchParameters searchParameters = DefaultRoutingSearchParameters(); searchParameters.set_first_solution_strategy( FirstSolutionStrategy::PARALLEL_CHEAPEST_INSERTION); // Solve the problem. const Assignment* solution = routing.SolveWithParameters(searchParameters); // Print solution on console. PrintSolution(data, manager, routing, *solution); } } // namespace operations_research int main(int /*argc*/, char* /*argv*/[]) { operations_research::VrpGlobalSpan(); 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.RoutingDimension; import com.google.ortools.constraintsolver.RoutingIndexManager; import com.google.ortools.constraintsolver.RoutingModel; import com.google.ortools.constraintsolver.RoutingSearchParameters; import com.google.ortools.constraintsolver.Solver; import com.google.ortools.constraintsolver.main; import java.util.logging.Logger; /** Minimal Pickup & Delivery Problem (PDP).*/ public class VrpPickupDelivery { private static final Logger logger = Logger.getLogger(VrpPickupDelivery.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 int[][] pickupsDeliveries = { {1, 6}, {2, 10}, {4, 3}, {5, 9}, {7, 8}, {15, 11}, {13, 12}, {16, 14}, }; 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. long totalDistance = 0; for (int i = 0; i < data.vehicleNumber; ++i) { long index = routing.start(i); logger.info("Route for Vehicle " + i + ":"); long routeDistance = 0; String route = ""; while (!routing.isEnd(index)) { route += manager.indexToNode(index) + " -> "; long previousIndex = index; index = solution.value(routing.nextVar(index)); routeDistance += routing.getArcCostForVehicle(previousIndex, index, i); } logger.info(route + manager.indexToNode(index)); logger.info("Distance of the route: " + routeDistance + "m"); totalDistance += routeDistance; } logger.info("Total Distance of all routes: " + totalDistance + "m"); } 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 Distance constraint. routing.addDimension(transitCallbackIndex, // transit callback index 0, // no slack 3000, // vehicle maximum travel distance true, // start cumul to zero "Distance"); RoutingDimension distanceDimension = routing.getMutableDimension("Distance"); distanceDimension.setGlobalSpanCostCoefficient(100); // Define Transportation Requests. Solver solver = routing.solver(); for (int[] request : data.pickupsDeliveries) { long pickupIndex = manager.nodeToIndex(request[0]); long deliveryIndex = manager.nodeToIndex(request[1]); routing.addPickupAndDelivery(pickupIndex, deliveryIndex); solver.addConstraint( solver.makeEquality(routing.vehicleVar(pickupIndex), routing.vehicleVar(deliveryIndex))); solver.addConstraint(solver.makeLessOrEqual( distanceDimension.cumulVar(pickupIndex), distanceDimension.cumulVar(deliveryIndex))); } // Setting first solution heuristic. RoutingSearchParameters searchParameters = main.defaultRoutingSearchParameters() .toBuilder() .setFirstSolutionStrategy(FirstSolutionStrategy.Value.PARALLEL_CHEAPEST_INSERTION) .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; /// <summary> /// Minimal Pickup & Delivery Problem (PDP). /// </summary> public class VrpPickupDelivery { 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 int[][] PickupsDeliveries = { new int[] { 1, 6 }, new int[] { 2, 10 }, new int[] { 4, 3 }, new int[] { 5, 9 }, new int[] { 7, 8 }, new int[] { 15, 11 }, new int[] { 13, 12 }, new int[] { 16, 14 }, }; 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. long totalDistance = 0; for (int i = 0; i < data.VehicleNumber; ++i) { Console.WriteLine("Route for Vehicle {0}:", i); long routeDistance = 0; var index = routing.Start(i); while (routing.IsEnd(index) == false) { Console.Write("{0} -> ", manager.IndexToNode((int)index)); 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; } Console.WriteLine("Total Distance of all routes: {0}m", totalDistance); } 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 Distance constraint. routing.AddDimension(transitCallbackIndex, 0, 3000, true, // start cumul to zero "Distance"); RoutingDimension distanceDimension = routing.GetMutableDimension("Distance"); distanceDimension.SetGlobalSpanCostCoefficient(100); // Define Transportation Requests. Solver solver = routing.solver(); for (int i = 0; i < data.PickupsDeliveries.GetLength(0); i++) { long pickupIndex = manager.NodeToIndex(data.PickupsDeliveries[i][0]); long deliveryIndex = manager.NodeToIndex(data.PickupsDeliveries[i][1]); routing.AddPickupAndDelivery(pickupIndex, deliveryIndex); solver.Add(solver.MakeEquality(routing.VehicleVar(pickupIndex), routing.VehicleVar(deliveryIndex))); solver.Add(solver.MakeLessOrEqual(distanceDimension.CumulVar(pickupIndex), distanceDimension.CumulVar(deliveryIndex))); } // Setting first solution heuristic. RoutingSearchParameters searchParameters = operations_research_constraint_solver.DefaultRoutingSearchParameters(); searchParameters.FirstSolutionStrategy = FirstSolutionStrategy.Types.Value.PathCheapestArc; // Solve the problem. Assignment solution = routing.SolveWithParameters(searchParameters); // Print solution on console. PrintSolution(data, routing, manager, solution); } }