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ortools-clone/examples/cpp/tsp.cc

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// Copyright 2018 Google LLC
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// 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.
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#include <vector>
#include <cmath>
#include "ortools/base/logging.h"
#include "ortools/constraint_solver/routing.h"
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namespace operations_research {
class DataProblem {
private:
std::vector<std::vector<int>> locations_;
public:
DataProblem() {
locations_ = {
{4, 4},
{2, 0}, {8, 0},
{0, 1}, {1, 1},
{5, 2}, {7, 2},
{3, 3}, {6, 3},
{5, 5}, {8, 5},
{1, 6}, {2, 6},
{3, 7}, {6, 7},
{0, 8}, {7, 8}
};
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// Compute locations in meters using the block dimension defined as follow
// Manhattan average block: 750ft x 264ft -> 228m x 80m
// here we use: 114m x 80m city block
// src: https://nyti.ms/2GDoRIe "NY Times: Know Your distance"
std::array<int, 2> cityBlock = {228/2, 80};
for (auto &i: locations_) {
i[0] = i[0] * cityBlock[0];
i[1] = i[1] * cityBlock[1];
}
}
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std::size_t GetVehicleNumber() const { return 1;}
const std::vector<std::vector<int>>& GetLocations() const { return locations_;}
RoutingModel::NodeIndex GetDepot() const { return RoutingModel::kFirstNode;}
};
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/*! @brief Manhattan distance implemented as a callback.
* @details It uses an array of positions and
* computes the Manhattan distance between the two positions of two different indices.*/
class ManhattanDistance: public RoutingModel::NodeEvaluator2 {
private:
std::vector<std::vector<int64>> distances_;
public:
ManhattanDistance(const DataProblem& data) {
// Precompute distance between location to have distance callback in O(1)
distances_ = std::vector<std::vector<int64>>(
data.GetLocations().size(),
std::vector<int64>(
data.GetLocations().size(),
0LL));
for (std::size_t fromNode = 0; fromNode < data.GetLocations().size(); fromNode++) {
for (std::size_t toNode = 0; toNode < data.GetLocations().size(); toNode++) {
if (fromNode != toNode)
distances_[fromNode][toNode] =
std::abs(data.GetLocations()[toNode][0] - data.GetLocations()[fromNode][0]) +
std::abs(data.GetLocations()[toNode][1] - data.GetLocations()[fromNode][1]);
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}
}
}
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bool IsRepeatable() const override {return true;}
//! @brief Returns the manhattan distance between the two nodes.
int64 Run(RoutingModel::NodeIndex FromNode, RoutingModel::NodeIndex ToNode) override {
return distances_[FromNode.value()][ToNode.value()];
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}
};
//! @brief Print the solution
//! @param[in] data Data of the problem.
//! @param[in] routing Routing solver used.
//! @param[in] solution Solution found by the solver.
void PrintSolution(
const DataProblem& data,
const RoutingModel& routing,
const Assignment& solution) {
LOG(INFO) << "Objective: " << solution.ObjectiveValue();
// Inspect solution.
int64 index = routing.Start(0);
LOG(INFO) << "Route for Vehicle 0:";
int64 distance = 0LL;
std::stringstream route;
while (routing.IsEnd(index) == false) {
route << routing.IndexToNode(index).value() << " -> ";
int64 previous_index = index;
index = solution.Value(routing.NextVar(index));
distance += const_cast<RoutingModel&>(routing).GetArcCostForVehicle(previous_index, index, 0LL);
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}
LOG(INFO) << route.str() << routing.IndexToNode(index).value();
LOG(INFO) << "Distance of the route: " << distance << "m";
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LOG(INFO) << "";
LOG(INFO) << "Advanced usage:";
LOG(INFO) << "Problem solved in " << routing.solver()->wall_time() << "ms";
}
void Solve() {
// Instantiate the data problem.
DataProblem data;
// Create Routing Model
RoutingModel routing(
data.GetLocations().size(),
data.GetVehicleNumber(),
data.GetDepot());
// Define weight of each edge
ManhattanDistance distance(data);
routing.SetArcCostEvaluatorOfAllVehicles(NewPermanentCallback(&distance, &ManhattanDistance::Run));
// Setting first solution heuristic (cheapest addition).
RoutingSearchParameters searchParameters = RoutingModel::DefaultSearchParameters();
searchParameters.set_first_solution_strategy(FirstSolutionStrategy::PATH_CHEAPEST_ARC);
const Assignment* solution = routing.SolveWithParameters(searchParameters);
PrintSolution(data, routing, *solution);
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}
} // namespace operations_research
int main(int argc, char** argv) {
google::InitGoogleLogging(argv[0]);
FLAGS_logtostderr = 1;
operations_research::Solve();
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return EXIT_SUCCESS;
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}