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// Copyright 2010-2018 Google LLC
// 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.
//
// Pickup and Delivery Problem with Time Windows.
// The overall objective is to minimize the length of the routes delivering
// quantities of goods between pickup and delivery locations, taking into
// account vehicle capacities and node time windows.
// Given a set of pairs of pickup and delivery nodes, find the set of routes
// visiting all the nodes, such that
// - corresponding pickup and delivery nodes are visited on the same route,
// - the pickup node is visited before the corresponding delivery node,
// - the quantity picked up at the pickup node is the same as the quantity
// delivered at the delivery node,
// - the total quantity carried by a vehicle at any time is less than its
// capacity,
// - each node must be visited within its time window (time range during which
// the node is accessible).
// The maximum number of vehicles used (i.e. the number of routes used) is
// specified in the data but can be overridden using the --pdp_force_vehicles
// flag.
//
// A further description of the problem can be found here:
// http://en.wikipedia.org/wiki/Vehicle_routing_problem
// http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.123.9965&rep=rep1&type=pdf.
// Reads data in the format defined by Li & Lim
// (https://www.sintef.no/projectweb/top/pdptw/li-lim-benchmark/documentation/).
#include <utility>
#include <vector>
#include "absl/strings/str_format.h"
#include "absl/strings/str_split.h"
#include "google/protobuf/text_format.h"
#include "ortools/base/commandlineflags.h"
#include "ortools/base/file.h"
#include "ortools/base/mathutil.h"
#include "ortools/base/timer.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"
#include "ortools/constraint_solver/routing_parameters.pb.h"
DEFINE_string(pdp_file, "",
"File containing the Pickup and Delivery Problem to solve.");
DEFINE_int32(pdp_force_vehicles, 0,
"Force the number of vehicles used (maximum number of routes.");
DEFINE_bool(reduce_vehicle_cost_model, true,
"Overrides the homonymous field of "
"DefaultRoutingModelParameters().");
DEFINE_string(routing_search_parameters,
"first_solution_strategy:ALL_UNPERFORMED",
"Text proto RoutingSearchParameters (possibly partial) that will "
"override the DefaultRoutingSearchParameters()");
namespace operations_research {
// Scaling factor used to scale up distances, allowing a bit more precision
// from Euclidean distances.
const int64 kScalingFactor = 1000;
// Vector of (x,y) node coordinates, *unscaled*, in some imaginary planar,
// metric grid.
typedef std::vector<std::pair<int, int> > Coordinates;
// Returns the scaled Euclidean distance between two nodes, coords holding the
// coordinates of the nodes.
int64 Travel(const Coordinates* const coords,
RoutingIndexManager::NodeIndex from,
RoutingIndexManager::NodeIndex to) {
DCHECK(coords != nullptr);
const int xd = coords->at(from.value()).first - coords->at(to.value()).first;
const int yd =
coords->at(from.value()).second - coords->at(to.value()).second;
return static_cast<int64>(kScalingFactor * sqrt(1.0L * xd * xd + yd * yd));
}
// Returns the scaled service time at a given node, service_times holding the
// service times.
int64 ServiceTime(const std::vector<int64>* const service_times,
RoutingIndexManager::NodeIndex node) {
return kScalingFactor * service_times->at(node.value());
}
// Returns the scaled (distance plus service time) between two indices, coords
// holding the coordinates of the nodes and service_times holding the service
// times.
// The service time is the time spent to execute a delivery or a pickup.
int64 TravelPlusServiceTime(const RoutingIndexManager& manager,
const Coordinates* const coords,
const std::vector<int64>* const service_times,
int64 from_index, int64 to_index) {
const RoutingIndexManager::NodeIndex from = manager.IndexToNode(from_index);
const RoutingIndexManager::NodeIndex to = manager.IndexToNode(to_index);
return ServiceTime(service_times, from) + Travel(coords, from, to);
}
// Returns the list of variables to use for the Tabu metaheuristic.
// The current list is:
// - Total cost of the solution,
// - Number of used vehicles,
// - Total schedule duration.
// TODO(user): add total waiting time.
std::vector<IntVar*> GetTabuVars(std::vector<IntVar*> existing_vars,
operations_research::RoutingModel* routing) {
Solver* const solver = routing->solver();
std::vector<IntVar*> vars(std::move(existing_vars));
vars.push_back(routing->CostVar());
IntVar* used_vehicles = solver->MakeIntVar(0, routing->vehicles());
std::vector<IntVar*> is_used_vars;
// Number of vehicle used
is_used_vars.reserve(routing->vehicles());
for (int v = 0; v < routing->vehicles(); v++) {
is_used_vars.push_back(solver->MakeIsDifferentCstVar(
routing->NextVar(routing->Start(v)), routing->End(v)));
}
solver->AddConstraint(
solver->MakeEquality(solver->MakeSum(is_used_vars), used_vehicles));
vars.push_back(used_vehicles);
return vars;
}
// Outputs a solution to the current model in a std::string.
std::string VerboseOutput(const RoutingModel& routing,
const RoutingIndexManager& manager,
const Assignment& assignment,
const Coordinates& coords,
const std::vector<int64>& service_times) {
std::string output;
const RoutingDimension& time_dimension = routing.GetDimensionOrDie("time");
const RoutingDimension& load_dimension = routing.GetDimensionOrDie("demand");
for (int i = 0; i < routing.vehicles(); ++i) {
absl::StrAppendFormat(&output, "Vehicle %d: ", i);
int64 index = routing.Start(i);
if (routing.IsEnd(assignment.Value(routing.NextVar(index)))) {
output.append("empty");
} else {
while (!routing.IsEnd(index)) {
absl::StrAppendFormat(&output, "%d ",
manager.IndexToNode(index).value());
const IntVar* vehicle = routing.VehicleVar(index);
absl::StrAppendFormat(&output, "Vehicle(%d) ",
assignment.Value(vehicle));
const IntVar* arrival = time_dimension.CumulVar(index);
absl::StrAppendFormat(&output, "Time(%d..%d) ", assignment.Min(arrival),
assignment.Max(arrival));
const IntVar* load = load_dimension.CumulVar(index);
absl::StrAppendFormat(&output, "Load(%d..%d) ", assignment.Min(load),
assignment.Max(load));
const int64 next_index = assignment.Value(routing.NextVar(index));
absl::StrAppendFormat(
&output, "Transit(%d) ",
TravelPlusServiceTime(manager, &coords, &service_times, index,
next_index));
index = next_index;
}
output.append("Route end ");
const IntVar* vehicle = routing.VehicleVar(index);
absl::StrAppendFormat(&output, "Vehicle(%d) ", assignment.Value(vehicle));
const IntVar* arrival = time_dimension.CumulVar(index);
absl::StrAppendFormat(&output, "Time(%d..%d) ", assignment.Min(arrival),
assignment.Max(arrival));
const IntVar* load = load_dimension.CumulVar(index);
absl::StrAppendFormat(&output, "Load(%d..%d) ", assignment.Min(load),
assignment.Max(load));
}
output.append("\n");
}
return output;
}
namespace {
// An inefficient but convenient method to parse a whitespace-separated list
// of integers. Returns true iff the input std::string was entirely valid and
// parsed.
bool SafeParseInt64Array(const std::string& str,
std::vector<int64>* parsed_int) {
std::istringstream input(str);
int64 x;
parsed_int->clear();
while (input >> x) parsed_int->push_back(x);
return input.eof();
}
} // namespace
// Builds and solves a model from a file in the format defined by Li & Lim
// (https://www.sintef.no/projectweb/top/pdptw/li-lim-benchmark/documentation/).
bool LoadAndSolve(const std::string& pdp_file,
const RoutingModelParameters& model_parameters,
const RoutingSearchParameters& search_parameters) {
// Load all the lines of the file in RAM (it shouldn't be too large anyway).
std::vector<std::string> lines;
{
std::string contents;
CHECK_OK(file::GetContents(pdp_file, &contents, file::Defaults()));
const int64 kMaxInputFileSize = 1 << 30; // 1GB
if (contents.size() >= kMaxInputFileSize) {
LOG(WARNING) << "Input file '" << pdp_file << "' is too large (>"
<< kMaxInputFileSize << " bytes).";
return false;
}
lines = absl::StrSplit(contents, '\n', absl::SkipEmpty());
}
// Reading header.
if (lines.empty()) {
LOG(WARNING) << "Empty file: " << pdp_file;
return false;
}
// Parse file header.
std::vector<int64> parsed_int;
if (!SafeParseInt64Array(lines[0], &parsed_int) || parsed_int.size() != 3 ||
parsed_int[0] < 0 || parsed_int[1] < 0 || parsed_int[2] < 0) {
LOG(WARNING) << "Malformed header: " << lines[0];
return false;
}
const int num_vehicles =
FLAGS_pdp_force_vehicles > 0 ? FLAGS_pdp_force_vehicles : parsed_int[0];
const int64 capacity = parsed_int[1];
// We do not care about the 'speed' field, in third position.
// Parse order data.
std::vector<int> customer_ids;
std::vector<std::pair<int, int> > coords;
std::vector<int64> demands;
std::vector<int64> open_times;
std::vector<int64> close_times;
std::vector<int64> service_times;
std::vector<RoutingIndexManager::NodeIndex> pickups;
std::vector<RoutingIndexManager::NodeIndex> deliveries;
int64 horizon = 0;
RoutingIndexManager::NodeIndex depot(0);
for (int line_index = 1; line_index < lines.size(); ++line_index) {
if (!SafeParseInt64Array(lines[line_index], &parsed_int) ||
parsed_int.size() != 9 || parsed_int[0] < 0 || parsed_int[4] < 0 ||
parsed_int[5] < 0 || parsed_int[6] < 0 || parsed_int[7] < 0 ||
parsed_int[8] < 0) {
LOG(WARNING) << "Malformed line #" << line_index << ": "
<< lines[line_index];
return false;
}
const int customer_id = parsed_int[0];
const int x = parsed_int[1];
const int y = parsed_int[2];
const int64 demand = parsed_int[3];
const int64 open_time = parsed_int[4];
const int64 close_time = parsed_int[5];
const int64 service_time = parsed_int[6];
const int pickup = parsed_int[7];
const int delivery = parsed_int[8];
customer_ids.push_back(customer_id);
coords.push_back(std::make_pair(x, y));
demands.push_back(demand);
open_times.push_back(open_time);
close_times.push_back(close_time);
service_times.push_back(service_time);
pickups.push_back(RoutingIndexManager::NodeIndex(pickup));
deliveries.push_back(RoutingIndexManager::NodeIndex(delivery));
if (pickup == 0 && delivery == 0) {
depot = RoutingIndexManager::NodeIndex(pickups.size() - 1);
}
horizon = std::max(horizon, close_time);
}
// Build pickup and delivery model.
const int num_nodes = customer_ids.size();
RoutingIndexManager manager(num_nodes, num_vehicles, depot);
RoutingModel routing(manager, model_parameters);
const int vehicle_cost =
routing.RegisterTransitCallback([&coords, &manager](int64 i, int64 j) {
return Travel(const_cast<const Coordinates*>(&coords),
manager.IndexToNode(i), manager.IndexToNode(j));
});
routing.SetArcCostEvaluatorOfAllVehicles(vehicle_cost);
RoutingTransitCallback2 demand_evaluator = [&](int64 from_index,
int64 to_index) {
return demands[manager.IndexToNode(from_index).value()];
};
routing.AddDimension(routing.RegisterTransitCallback(demand_evaluator), 0,
capacity, /*fix_start_cumul_to_zero=*/true, "demand");
RoutingTransitCallback2 time_evaluator = [&](int64 from_index,
int64 to_index) {
return TravelPlusServiceTime(manager, &coords, &service_times, from_index,
to_index);
};
routing.AddDimension(routing.RegisterTransitCallback(time_evaluator),
kScalingFactor * horizon, kScalingFactor * horizon,
/*fix_start_cumul_to_zero=*/true, "time");
const RoutingDimension& time_dimension = routing.GetDimensionOrDie("time");
Solver* const solver = routing.solver();
for (int node = 0; node < num_nodes; ++node) {
const int64 index =
manager.NodeToIndex(RoutingIndexManager::NodeIndex(node));
if (pickups[node] == 0 && deliveries[node] != 0) {
const int64 delivery_index = manager.NodeToIndex(deliveries[node]);
solver->AddConstraint(solver->MakeEquality(
routing.VehicleVar(index), routing.VehicleVar(delivery_index)));
solver->AddConstraint(
solver->MakeLessOrEqual(time_dimension.CumulVar(index),
time_dimension.CumulVar(delivery_index)));
routing.AddPickupAndDelivery(index,
manager.NodeToIndex(deliveries[node]));
}
IntVar* const cumul = time_dimension.CumulVar(index);
cumul->SetMin(kScalingFactor * open_times[node]);
cumul->SetMax(kScalingFactor * close_times[node]);
}
if (search_parameters.local_search_metaheuristic() ==
LocalSearchMetaheuristic::GENERIC_TABU_SEARCH) {
// Create variable for the total schedule time of the solution.
// This will be used as one of the Tabu criteria.
// This is done here and not in GetTabuVarsCallback as it requires calling
// AddVariableMinimizedByFinalizer and this method must be called early.
std::vector<IntVar*> end_cumuls;
std::vector<IntVar*> start_cumuls;
for (int i = 0; i < routing.vehicles(); ++i) {
end_cumuls.push_back(time_dimension.CumulVar(routing.End(i)));
start_cumuls.push_back(time_dimension.CumulVar(routing.Start(i)));
}
IntVar* total_time = solver->MakeIntVar(0, 99999999, "total");
solver->AddConstraint(solver->MakeEquality(
solver->MakeDifference(solver->MakeSum(end_cumuls),
solver->MakeSum(start_cumuls)),
total_time));
routing.AddVariableMinimizedByFinalizer(total_time);
RoutingModel::GetTabuVarsCallback tabu_var_callback =
[total_time](RoutingModel* model) {
return GetTabuVars({total_time}, model);
};
routing.SetTabuVarsCallback(tabu_var_callback);
}
// Adding penalty costs to allow skipping orders.
const int64 kPenalty = 10000000;
for (RoutingIndexManager::NodeIndex order(1); order < routing.nodes();
++order) {
std::vector<int64> orders(1, manager.NodeToIndex(order));
routing.AddDisjunction(orders, kPenalty);
}
// Solve pickup and delivery problem.
SimpleCycleTimer timer;
timer.Start();
const Assignment* assignment = routing.SolveWithParameters(search_parameters);
timer.Stop();
LOG(INFO) << routing.solver()->LocalSearchProfile();
if (nullptr != assignment) {
LOG(INFO) << VerboseOutput(routing, manager, *assignment, coords,
service_times);
LOG(INFO) << "Cost: " << assignment->ObjectiveValue();
int skipped_nodes = 0;
for (int node = 0; node < routing.Size(); node++) {
if (!routing.IsEnd(node) && !routing.IsStart(node) &&
assignment->Value(routing.NextVar(node)) == node) {
skipped_nodes++;
}
}
LOG(INFO) << "Number of skipped nodes: " << skipped_nodes;
int num_used_vehicles = 0;
for (int v = 0; v < routing.vehicles(); v++) {
if (routing.IsVehicleUsed(*assignment, v)) {
num_used_vehicles++;
}
}
LOG(INFO) << "Number of used vehicles: " << num_used_vehicles;
LOG(INFO) << "Time: " << timer.Get();
return true;
}
return false;
}
} // namespace operations_research
int main(int argc, char** argv) {
absl::SetFlag(&FLAGS_logtostderr, true);
gflags::ParseCommandLineFlags(&argc, &argv, true);
operations_research::RoutingModelParameters model_parameters =
operations_research::DefaultRoutingModelParameters();
model_parameters.set_reduce_vehicle_cost_model(
FLAGS_reduce_vehicle_cost_model);
operations_research::RoutingSearchParameters search_parameters =
operations_research::DefaultRoutingSearchParameters();
CHECK(google::protobuf::TextFormat::MergeFromString(
FLAGS_routing_search_parameters, &search_parameters));
if (!operations_research::LoadAndSolve(FLAGS_pdp_file, model_parameters,
search_parameters)) {
LOG(INFO) << "Error solving " << FLAGS_pdp_file;
}
return EXIT_SUCCESS;
}
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