190 lines
8.1 KiB
C++
190 lines
8.1 KiB
C++
// Copyright 2010-2021 Google LLC
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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// Capacitated Vehicle Routing Problem with Time Windows and capacitated
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// resources.
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// This is an extension to the model in cvrptw.cc so refer to that file for
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// more information on the common part of the model. The model implemented here
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// limits the number of vehicles which can simultaneously leave or enter the
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// depot due to limited resources (or capacity) available.
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// TODO(user): The current model consumes resources even for vehicles with
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// empty routes; fix this when we have an API on the cumulative constraints
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// with variable demands.
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#include <cstdint>
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#include <vector>
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#include "absl/flags/parse.h"
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#include "absl/flags/usage.h"
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#include "absl/random/random.h"
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#include "examples/cpp/cvrptw_lib.h"
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#include "google/protobuf/text_format.h"
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#include "ortools/base/commandlineflags.h"
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#include "ortools/base/integral_types.h"
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#include "ortools/base/logging.h"
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#include "ortools/constraint_solver/routing.h"
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#include "ortools/constraint_solver/routing_index_manager.h"
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#include "ortools/constraint_solver/routing_parameters.h"
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#include "ortools/constraint_solver/routing_parameters.pb.h"
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using operations_research::Assignment;
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using operations_research::DefaultRoutingSearchParameters;
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using operations_research::GetSeed;
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using operations_research::IntervalVar;
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using operations_research::IntVar;
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using operations_research::LocationContainer;
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using operations_research::RandomDemand;
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using operations_research::RoutingDimension;
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using operations_research::RoutingIndexManager;
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using operations_research::RoutingModel;
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using operations_research::RoutingNodeIndex;
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using operations_research::RoutingSearchParameters;
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using operations_research::ServiceTimePlusTransition;
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using operations_research::Solver;
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ABSL_FLAG(int, vrp_orders, 100, "Nodes in the problem.");
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ABSL_FLAG(int, vrp_vehicles, 20,
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"Size of Traveling Salesman Problem instance.");
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ABSL_FLAG(bool, vrp_use_deterministic_random_seed, false,
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"Use deterministic random seeds.");
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ABSL_FLAG(std::string, routing_search_parameters, "",
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"Text proto RoutingSearchParameters (possibly partial) that will "
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"override the DefaultRoutingSearchParameters()");
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const char* kTime = "Time";
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const char* kCapacity = "Capacity";
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int main(int argc, char** argv) {
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google::InitGoogleLogging(argv[0]);
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absl::ParseCommandLine(argc, argv);
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CHECK_LT(0, absl::GetFlag(FLAGS_vrp_orders))
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<< "Specify an instance size greater than 0.";
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CHECK_LT(0, absl::GetFlag(FLAGS_vrp_vehicles))
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<< "Specify a non-null vehicle fleet size.";
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// VRP of size absl::GetFlag(FLAGS_vrp_size).
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// Nodes are indexed from 0 to absl::GetFlag(FLAGS_vrp_orders), the starts and
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// ends of the routes are at node 0.
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const RoutingIndexManager::NodeIndex kDepot(0);
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RoutingIndexManager manager(absl::GetFlag(FLAGS_vrp_orders) + 1,
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absl::GetFlag(FLAGS_vrp_vehicles), kDepot);
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RoutingModel routing(manager);
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// Setting up locations.
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const int64_t kXMax = 100000;
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const int64_t kYMax = 100000;
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const int64_t kSpeed = 10;
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LocationContainer locations(
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kSpeed, absl::GetFlag(FLAGS_vrp_use_deterministic_random_seed));
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for (int location = 0; location <= absl::GetFlag(FLAGS_vrp_orders);
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++location) {
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locations.AddRandomLocation(kXMax, kYMax);
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}
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// Setting the cost function.
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const int vehicle_cost = routing.RegisterTransitCallback(
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[&locations, &manager](int64_t i, int64_t j) {
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return locations.ManhattanDistance(manager.IndexToNode(i),
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manager.IndexToNode(j));
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});
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routing.SetArcCostEvaluatorOfAllVehicles(vehicle_cost);
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// Adding capacity dimension constraints.
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const int64_t kVehicleCapacity = 40;
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const int64_t kNullCapacitySlack = 0;
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RandomDemand demand(manager.num_nodes(), kDepot,
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absl::GetFlag(FLAGS_vrp_use_deterministic_random_seed));
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demand.Initialize();
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routing.AddDimension(routing.RegisterTransitCallback(
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[&demand, &manager](int64_t i, int64_t j) {
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return demand.Demand(manager.IndexToNode(i),
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manager.IndexToNode(j));
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}),
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kNullCapacitySlack, kVehicleCapacity,
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/*fix_start_cumul_to_zero=*/true, kCapacity);
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// Adding time dimension constraints.
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const int64_t kTimePerDemandUnit = 300;
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const int64_t kHorizon = 24 * 3600;
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ServiceTimePlusTransition time(
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kTimePerDemandUnit,
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[&demand](RoutingNodeIndex i, RoutingNodeIndex j) {
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return demand.Demand(i, j);
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},
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[&locations](RoutingNodeIndex i, RoutingNodeIndex j) {
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return locations.ManhattanTime(i, j);
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});
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routing.AddDimension(
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routing.RegisterTransitCallback([&time, &manager](int64_t i, int64_t j) {
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return time.Compute(manager.IndexToNode(i), manager.IndexToNode(j));
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}),
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kHorizon, kHorizon, /*fix_start_cumul_to_zero=*/false, kTime);
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const RoutingDimension& time_dimension = routing.GetDimensionOrDie(kTime);
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// Adding time windows.
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std::mt19937 randomizer(
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GetSeed(absl::GetFlag(FLAGS_vrp_use_deterministic_random_seed)));
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const int64_t kTWDuration = 5 * 3600;
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for (int order = 1; order < manager.num_nodes(); ++order) {
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const int64_t start =
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absl::Uniform<int32_t>(randomizer, 0, kHorizon - kTWDuration);
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time_dimension.CumulVar(order)->SetRange(start, start + kTWDuration);
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}
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// Adding resource constraints at the depot (start and end location of
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// routes).
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std::vector<IntVar*> start_end_times;
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for (int i = 0; i < absl::GetFlag(FLAGS_vrp_vehicles); ++i) {
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start_end_times.push_back(time_dimension.CumulVar(routing.End(i)));
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start_end_times.push_back(time_dimension.CumulVar(routing.Start(i)));
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}
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// Build corresponding time intervals.
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const int64_t kVehicleSetup = 180;
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Solver* const solver = routing.solver();
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std::vector<IntervalVar*> intervals;
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solver->MakeFixedDurationIntervalVarArray(start_end_times, kVehicleSetup,
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"depot_interval", &intervals);
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// Constrain the number of maximum simultaneous intervals at depot.
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const int64_t kDepotCapacity = 5;
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std::vector<int64_t> depot_usage(start_end_times.size(), 1);
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solver->AddConstraint(
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solver->MakeCumulative(intervals, depot_usage, kDepotCapacity, "depot"));
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// Instantiate route start and end times to produce feasible times.
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for (int i = 0; i < start_end_times.size(); ++i) {
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routing.AddVariableMinimizedByFinalizer(start_end_times[i]);
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}
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// Adding penalty costs to allow skipping orders.
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const int64_t kPenalty = 100000;
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const RoutingIndexManager::NodeIndex kFirstNodeAfterDepot(1);
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for (RoutingIndexManager::NodeIndex order = kFirstNodeAfterDepot;
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order < manager.num_nodes(); ++order) {
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std::vector<int64_t> orders(1, manager.NodeToIndex(order));
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routing.AddDisjunction(orders, kPenalty);
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}
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// Solve, returns a solution if any (owned by RoutingModel).
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RoutingSearchParameters parameters = DefaultRoutingSearchParameters();
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CHECK(google::protobuf::TextFormat::MergeFromString(
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absl::GetFlag(FLAGS_routing_search_parameters), ¶meters));
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const Assignment* solution = routing.SolveWithParameters(parameters);
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if (solution != nullptr) {
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DisplayPlan(manager, routing, *solution, /*use_same_vehicle_costs=*/false,
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/*max_nodes_per_group=*/0, /*same_vehicle_cost=*/0,
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routing.GetDimensionOrDie(kCapacity),
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routing.GetDimensionOrDie(kTime));
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} else {
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LOG(INFO) << "No solution found.";
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}
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return EXIT_SUCCESS;
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}
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