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ortools-clone/examples/cpp/cvrptw.cc
Laurent Perron 70e73d8754 clang-format
2018-06-08 16:40:43 +02:00

152 lines
6.2 KiB
C++

// 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 <vector>
#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<RoutingModel::NodeIndex> orders(1, order);
routing.AddDisjunction(orders, kPenalty);
}
// Adding same vehicle constraint costs for consecutive nodes.
if (FLAGS_vrp_use_same_vehicle_costs) {
std::vector<RoutingModel::NodeIndex> 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;
}