// Copyright 2010-2017 Google // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. // // Capacitated Vehicle Routing Problem with Time Windows (and optional orders). // A description of the problem can be found here: // http://en.wikipedia.org/wiki/Vehicle_routing_problem. // The variant which is tackled by this model includes a capacity dimension, // time windows and optional orders, with a penalty cost if orders are not // performed. For the sake of simplicty, orders are randomly located and // distances are computed using the Manhattan distance. Distances are assumed // to be in meters and times in seconds. #include #include "examples/cpp/cvrptw_lib.h" #include "ortools/base/callback.h" #include "ortools/base/commandlineflags.h" #include "ortools/base/integral_types.h" #include "ortools/base/logging.h" #include "ortools/base/random.h" #include "ortools/constraint_solver/routing.h" #include "ortools/constraint_solver/routing_enums.pb.h" #include "ortools/constraint_solver/routing_flags.h" using operations_research::ACMRandom; using operations_research::GetSeed; using operations_research::LocationContainer; using operations_research::RandomDemand; using operations_research::RoutingModel; using operations_research::RoutingSearchParameters; using operations_research::ServiceTimePlusTransition; DEFINE_int32(vrp_orders, 100, "Nodes in the problem."); DEFINE_int32(vrp_vehicles, 20, "Size of Traveling Salesman Problem instance."); DEFINE_bool(vrp_use_deterministic_random_seed, false, "Use deterministic random seeds."); DEFINE_bool(vrp_use_same_vehicle_costs, false, "Use same vehicle costs in the routing model"); const char* kTime = "Time"; const char* kCapacity = "Capacity"; const int64 kMaxNodesPerGroup = 10; const int64 kSameVehicleCost = 1000; int main(int argc, char** argv) { gflags::ParseCommandLineFlags(&argc, &argv, true); CHECK_LT(0, FLAGS_vrp_orders) << "Specify an instance size greater than 0."; CHECK_LT(0, FLAGS_vrp_vehicles) << "Specify a non-null vehicle fleet size."; // VRP of size FLAGS_vrp_size. // Nodes are indexed from 0 to FLAGS_vrp_orders, the starts and ends of // the routes are at node 0. const RoutingModel::NodeIndex kDepot(0); RoutingModel routing(FLAGS_vrp_orders + 1, FLAGS_vrp_vehicles, kDepot); RoutingSearchParameters parameters = operations_research::BuildSearchParametersFromFlags(); parameters.set_first_solution_strategy( operations_research::FirstSolutionStrategy::PATH_CHEAPEST_ARC); parameters.mutable_local_search_operators()->set_use_path_lns(false); // Setting up locations. const int64 kXMax = 100000; const int64 kYMax = 100000; const int64 kSpeed = 10; LocationContainer locations(kSpeed, FLAGS_vrp_use_deterministic_random_seed); for (int location = 0; location <= FLAGS_vrp_orders; ++location) { locations.AddRandomLocation(kXMax, kYMax); } // Setting the cost function. routing.SetArcCostEvaluatorOfAllVehicles( NewPermanentCallback(&locations, &LocationContainer::ManhattanDistance)); // Adding capacity dimension constraints. const int64 kVehicleCapacity = 40; const int64 kNullCapacitySlack = 0; RandomDemand demand(routing.nodes(), kDepot, FLAGS_vrp_use_deterministic_random_seed); demand.Initialize(); routing.AddDimension(NewPermanentCallback(&demand, &RandomDemand::Demand), kNullCapacitySlack, kVehicleCapacity, /*fix_start_cumul_to_zero=*/true, kCapacity); // Adding time dimension constraints. const int64 kTimePerDemandUnit = 300; const int64 kHorizon = 24 * 3600; ServiceTimePlusTransition time( kTimePerDemandUnit, NewPermanentCallback(&demand, &RandomDemand::Demand), NewPermanentCallback(&locations, &LocationContainer::ManhattanTime)); routing.AddDimension( NewPermanentCallback(&time, &ServiceTimePlusTransition::Compute), kHorizon, kHorizon, /*fix_start_cumul_to_zero=*/true, kTime); const operations_research::RoutingDimension& time_dimension = routing.GetDimensionOrDie(kTime); // Adding time windows. ACMRandom randomizer(GetSeed(FLAGS_vrp_use_deterministic_random_seed)); const int64 kTWDuration = 5 * 3600; for (int order = 1; order < routing.nodes(); ++order) { const int64 start = randomizer.Uniform(kHorizon - kTWDuration); time_dimension.CumulVar(order)->SetRange(start, start + kTWDuration); } // Adding penalty costs to allow skipping orders. const int64 kPenalty = 10000000; const RoutingModel::NodeIndex kFirstNodeAfterDepot(1); for (RoutingModel::NodeIndex order = kFirstNodeAfterDepot; order < routing.nodes(); ++order) { std::vector orders(1, order); routing.AddDisjunction(orders, kPenalty); } // Adding same vehicle constraint costs for consecutive nodes. if (FLAGS_vrp_use_same_vehicle_costs) { std::vector group; for (RoutingModel::NodeIndex order = kFirstNodeAfterDepot; order < routing.nodes(); ++order) { group.push_back(order); if (group.size() == kMaxNodesPerGroup) { routing.AddSoftSameVehicleConstraint(group, kSameVehicleCost); group.clear(); } } if (!group.empty()) { routing.AddSoftSameVehicleConstraint(group, kSameVehicleCost); } } // Solve, returns a solution if any (owned by RoutingModel). const operations_research::Assignment* solution = routing.SolveWithParameters(parameters); if (solution != nullptr) { DisplayPlan(routing, *solution, FLAGS_vrp_use_same_vehicle_costs, kMaxNodesPerGroup, kSameVehicleCost, routing.GetDimensionOrDie(kCapacity), routing.GetDimensionOrDie(kTime)); } else { LOG(INFO) << "No solution found."; } return 0; }