153 lines
5.3 KiB
C++
153 lines
5.3 KiB
C++
// Copyright 2010-2022 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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// [START program]
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// [START import]
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#include <cmath>
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#include <cstdint>
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#include <vector>
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#include "ortools/constraint_solver/routing.h"
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#include "ortools/constraint_solver/routing_enums.pb.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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// [END import]
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namespace operations_research {
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// [START data_model]
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struct DataModel {
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const std::vector<std::vector<int>> locations{
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{4, 4}, {2, 0}, {8, 0}, {0, 1}, {1, 1}, {5, 2}, {7, 2}, {3, 3}, {6, 3},
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{5, 5}, {8, 5}, {1, 6}, {2, 6}, {3, 7}, {6, 7}, {0, 8}, {7, 8},
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};
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const int num_vehicles = 1;
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const RoutingIndexManager::NodeIndex depot{0};
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DataModel() {
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// Convert locations in meters using a city block dimension of 114m x 80m.
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for (auto& it : const_cast<std::vector<std::vector<int>>&>(locations)) {
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it[0] *= 114;
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it[1] *= 80;
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}
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}
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};
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// [END data_model]
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// [START manhattan_distance_matrix]
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/*! @brief Generate Manhattan distance matrix.
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* @details It uses the data.locations to computes the Manhattan distance
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* between the two positions of two different indices.*/
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std::vector<std::vector<int64_t>> GenerateManhattanDistanceMatrix(
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const std::vector<std::vector<int>>& locations) {
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std::vector<std::vector<int64_t>> distances =
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std::vector<std::vector<int64_t>>(
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locations.size(), std::vector<int64_t>(locations.size(), int64_t{0}));
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for (int fromNode = 0; fromNode < locations.size(); fromNode++) {
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for (int toNode = 0; toNode < locations.size(); toNode++) {
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if (fromNode != toNode)
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distances[fromNode][toNode] =
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int64_t{std::abs(locations[toNode][0] - locations[fromNode][0]) +
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std::abs(locations[toNode][1] - locations[fromNode][1])};
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}
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}
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return distances;
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}
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// [END manhattan_distance_matrix]
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// [START solution_printer]
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//! @brief Print the solution
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//! @param[in] manager Index manager used.
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//! @param[in] routing Routing solver used.
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//! @param[in] solution Solution found by the solver.
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void PrintSolution(const RoutingIndexManager& manager,
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const RoutingModel& routing, const Assignment& solution) {
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LOG(INFO) << "Objective: " << solution.ObjectiveValue();
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// Inspect solution.
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int64_t index = routing.Start(0);
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LOG(INFO) << "Route for Vehicle 0:";
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int64_t distance{0};
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std::stringstream route;
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while (routing.IsEnd(index) == false) {
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route << manager.IndexToNode(index).value() << " -> ";
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int64_t previous_index = index;
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index = solution.Value(routing.NextVar(index));
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distance += routing.GetArcCostForVehicle(previous_index, index, int64_t{0});
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}
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LOG(INFO) << route.str() << manager.IndexToNode(index).value();
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LOG(INFO) << "Distance of the route: " << distance << "m";
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LOG(INFO) << "";
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LOG(INFO) << "Advanced usage:";
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LOG(INFO) << "Problem solved in " << routing.solver()->wall_time() << "ms";
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}
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// [END solution_printer]
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void Tsp() {
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// Instantiate the data problem.
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// [START data]
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DataModel data;
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// [END data]
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// Create Routing Index Manager
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// [START index_manager]
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RoutingIndexManager manager(data.locations.size(), data.num_vehicles,
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data.depot);
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// [END index_manager]
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// Create Routing Model.
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// [START routing_model]
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RoutingModel routing(manager);
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// [END routing_model]
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// Create and register a transit callback.
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// [START transit_callback]
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const auto distance_matrix = GenerateManhattanDistanceMatrix(data.locations);
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const int transit_callback_index = routing.RegisterTransitCallback(
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[&distance_matrix, &manager](int64_t from_index,
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int64_t to_index) -> int64_t {
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// Convert from routing variable Index to distance matrix NodeIndex.
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auto from_node = manager.IndexToNode(from_index).value();
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auto to_node = manager.IndexToNode(to_index).value();
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return distance_matrix[from_node][to_node];
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});
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// [END transit_callback]
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// Define cost of each arc.
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// [START arc_cost]
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routing.SetArcCostEvaluatorOfAllVehicles(transit_callback_index);
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// [END arc_cost]
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// Setting first solution heuristic.
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// [START parameters]
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RoutingSearchParameters searchParameters = DefaultRoutingSearchParameters();
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searchParameters.set_first_solution_strategy(
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FirstSolutionStrategy::PATH_CHEAPEST_ARC);
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// [END parameters]
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// Solve the problem.
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// [START solve]
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const Assignment* solution = routing.SolveWithParameters(searchParameters);
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// [END solve]
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// Print solution on console.
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// [START print_solution]
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PrintSolution(manager, routing, *solution);
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// [END print_solution]
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}
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} // namespace operations_research
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int main(int argc, char** argv) {
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operations_research::Tsp();
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return EXIT_SUCCESS;
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}
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// [END program]
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