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ortools-clone/examples/tests/remote/tsp.cc
2025-12-15 15:28:50 +01:00

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// Copyright 2010-2025 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.
//
// Traveling Salesman Sample.
//
// This is a sample using the routing library to solve a Traveling Salesman
// Problem.
// The description of the problem can be found here:
// http://en.wikipedia.org/wiki/Travelling_salesman_problem.
// For small problems one can use the hamiltonian path library directly (cf
// graph/hamiltonian_path.h).
// The optimization engine uses local search to improve solutions, first
// solutions being generated using a cheapest addition heuristic.
// Optionally one can randomly forbid a set of random connections between nodes
// (forbidden arcs).
#include "base/callback.h"
#include "base/commandlineflags.h"
#include "base/join.h"
#include "base/random.h"
#include "base/types.h"
#include "base/unique_ptr.h"
#include "constraint_solver/routing.h"
using operations_research::ACMRandom;
using operations_research::Assignment;
using operations_research::RoutingModel;
using operations_research::scoped_ptr;
using operations_research::StrCat;
DEFINE_int32(tsp_size, 10, "Size of Traveling Salesman Problem instance.");
DEFINE_bool(tsp_use_random_matrix, true, "Use random cost matrix.");
DEFINE_int32(tsp_random_forbidden_connections, 0,
"Number of random forbidden connections.");
DEFINE_bool(tsp_use_deterministic_random_seed, false,
"Use deterministic random seeds.");
DECLARE_string(routing_first_solution);
DECLARE_bool(routing_no_lns);
// Random seed generator.
int32_t GetSeed() {
if (absl::GetFlag(FLAGS_tsp_use_deterministic_random_seed)) {
return ACMRandom::DeterministicSeed();
} else {
return ACMRandom::HostnamePidTimeSeed();
}
}
// Cost/distance functions.
// Sample function.
int64_t MyDistance(RoutingModel::NodeIndex from, RoutingModel::NodeIndex to) {
// Put your distance code here.
return (from + to).value(); // for instance
}
// Random matrix.
class RandomMatrix {
public:
explicit RandomMatrix(int size) : size_(size) {}
void Initialize() {
matrix_.reset(new int64_t[size_ * size_]);
const int64_t kDistanceMax = 100;
ACMRandom randomizer(GetSeed());
for (RoutingModel::NodeIndex from = RoutingModel::kFirstNode; from < size_;
++from) {
for (RoutingModel::NodeIndex to = RoutingModel::kFirstNode; to < size_;
++to) {
if (to != from) {
matrix_[MatrixIndex(from, to)] = randomizer.Uniform(kDistanceMax);
} else {
matrix_[MatrixIndex(from, to)] = 0LL;
}
}
}
}
int64_t Distance(RoutingModel::NodeIndex from,
RoutingModel::NodeIndex to) const {
return matrix_[MatrixIndex(from, to)];
}
private:
int64_t MatrixIndex(RoutingModel::NodeIndex from,
RoutingModel::NodeIndex to) const {
return (from * size_ + to).value();
}
std::unique_ptr<int64_t[]> matrix_;
const int size_;
};
int main(int argc, char** argv) {
google::ParseCommandLineFlags(&argc, &argv, true);
if (absl::GetFlag(FLAGS_tsp_size) > 0) {
// TSP of size absl::GetFlag(FLAGS_tsp_size).
// Second argument = 1 to build a single tour (it's a TSP).
// Nodes are indexed from 0 to absl::GetFlag(FLAGS_tsp_size) - 1, by default
// the start of the route is node 0.
RoutingModel routing(absl::GetFlag(FLAGS_tsp_size), 1);
// Setting first solution heuristic (cheapest addition).
absl::GetFlag(FLAGS_routing_first_solution) = "PathCheapestArc";
// Disabling Large Neighborhood Search, comment out to activate it.
absl::GetFlag(FLAGS_routing_no_lns) = true;
// Setting the cost function.
// Put a permanent callback to the distance accessor here. The callback
// has the following signature: ResultCallback2<int64_t, int64_t, int64_t>.
// The two arguments are the from and to node inidices.
RandomMatrix matrix(absl::GetFlag(FLAGS_tsp_size));
if (absl::GetFlag(FLAGS_tsp_use_random_matrix)) {
matrix.Initialize();
routing.SetArcCostEvaluatorOfAllVehicles(
NewPermanentCallback(&matrix, &RandomMatrix::Distance));
} else {
routing.SetArcCostEvaluatorOfAllVehicles(
NewPermanentCallback(MyDistance));
}
// Forbid node connections (randomly).
ACMRandom randomizer(GetSeed());
int64_t forbidden_connections = 0;
while (forbidden_connections <
absl::GetFlag(FLAGS_tsp_random_forbidden_connections)) {
const int64_t from =
randomizer.Uniform(absl::GetFlag(FLAGS_tsp_size) - 1);
const int64_t to =
randomizer.Uniform(absl::GetFlag(FLAGS_tsp_size) - 1) + 1;
if (routing.NextVar(from)->Contains(to)) {
LOG(INFO) << "Forbidding connection " << from << " -> " << to;
routing.NextVar(from)->RemoveValue(to);
++forbidden_connections;
}
}
// Solve, returns a solution if any (owned by RoutingModel).
const Assignment* solution = routing.Solve();
if (solution != NULL) {
// Solution cost.
LOG(INFO) << "Cost " << solution->ObjectiveValue();
// Inspect solution.
// Only one route here; otherwise iterate from 0 to routing.vehicles() - 1
const int route_number = 0;
std::string route;
for (int64_t node = routing.Start(route_number); !routing.IsEnd(node);
node = solution->Value(routing.NextVar(node))) {
route = StrCat(route, StrCat(node, " -> "));
}
route = StrCat(route, "0");
LOG(INFO) << route;
} else {
LOG(INFO) << "No solution found.";
}
} else {
LOG(INFO) << "Specify an instance size greater than 0.";
}
return 0;
}