osrm-backend/routing_algorithms/tsp_nearest_neighbour.hpp

/*

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*/

#ifndef TSP_NEAREST_NEIGHBOUR_HPP
#define TSP_NEAREST_NEIGHBOUR_HPP


#include "../data_structures/search_engine.hpp"
#include "../util/string_util.hpp"
#include "../util/simple_logger.hpp"

#include <osrm/json_container.hpp>

#include <cstdlib>
#include <algorithm>
#include <string>
#include <vector>
#include <limits>



namespace osrm
{
namespace tsp
{

std::vector<NodeID> NearestNeighbourTSP(const std::vector<NodeID> & locations,
                                        const std::size_t number_of_locations,
                                        const std::vector<EdgeWeight> & dist_table) {
    //////////////////////////////////////////////////////////////////////////////////////////////////
    // START GREEDY NEAREST NEIGHBOUR HERE
    // 1. grab a random location and mark as starting point
    // 2. find the nearest unvisited neighbour, set it as the current location and mark as visited
    // 3. repeat 2 until there is no unvisited location
    // 4. return route back to starting point
    // 5. compute route
    // 6. repeat 1-5 with different starting points and choose iteration with shortest trip
    // 7. DONE!
    //////////////////////////////////////////////////////////////////////////////////////////////////
    std::vector<NodeID> route;
    route.reserve(number_of_locations);

    const int component_size = locations.size();
    int shortest_trip_distance = INVALID_EDGE_WEIGHT;

    // ALWAYS START AT ANOTHER STARTING POINT
    for(auto start_node : locations)
    {
        int curr_node = start_node;

        std::vector<NodeID> curr_route;
        curr_route.reserve(component_size);
        curr_route.push_back(start_node);

        // visited[i] indicates whether node i was already visited by the salesman
        std::vector<bool> visited(number_of_locations, false);
        visited[start_node] = true;

        // 3. REPEAT FOR EVERY UNVISITED NODE
        int trip_dist = 0;
        for(int via_point = 1; via_point < component_size; ++via_point)
        {
            int min_dist = INVALID_EDGE_WEIGHT;
            int min_id = -1;

            // 2. FIND NEAREST NEIGHBOUR
            for (auto next : locations) {
                if(!visited[next] &&
                   *(dist_table.begin() + curr_node * number_of_locations + next) < min_dist) {
                    min_dist = *(dist_table.begin() + curr_node * number_of_locations + next);
                    min_id = next;
                }
            }
            visited[min_id] = true;
            curr_route.push_back(min_id);
            trip_dist += min_dist;
            curr_node = min_id;
        }

        // check round trip with this starting point is shorter than the shortest round trip found till now
        if (trip_dist < shortest_trip_distance) {
            shortest_trip_distance = trip_dist;
            route = curr_route;
        }
    }
    return route;
}

std::vector<NodeID> NearestNeighbourTSP(const std::size_t number_of_locations,
                                        const std::vector<EdgeWeight> & dist_table) {
    //////////////////////////////////////////////////////////////////////////////////////////////////
    // START GREEDY NEAREST NEIGHBOUR HERE
    // 1. grab a random location and mark as starting point
    // 2. find the nearest unvisited neighbour, set it as the current location and mark as visited
    // 3. repeat 2 until there is no unvisited location
    // 4. return route back to starting point
    // 5. compute route
    // 6. repeat 1-5 with different starting points and choose iteration with shortest trip
    // 7. DONE!
    //////////////////////////////////////////////////////////////////////////////////////////////////

    std::vector<NodeID> route;
    route.reserve(number_of_locations);

    int shortest_trip_distance = INVALID_EDGE_WEIGHT;

    // ALWAYS START AT ANOTHER STARTING POINT
    for(int start_node = 0; start_node < number_of_locations; ++start_node)
    {
        int curr_node = start_node;

        std::vector<NodeID> curr_route;
        curr_route.reserve(number_of_locations);
        curr_route.push_back(start_node);

        // visited[i] indicates whether node i was already visited by the salesman
        std::vector<bool> visited(number_of_locations, false);
        visited[start_node] = true;

        // 3. REPEAT FOR EVERY UNVISITED NODE
        int trip_dist = 0;
        for(int via_point = 1; via_point < number_of_locations; ++via_point)
        {
            int min_dist = INVALID_EDGE_WEIGHT;
            int min_id = -1;

            // 2. FIND NEAREST NEIGHBOUR
            auto row_begin_iterator = dist_table.begin() + (curr_node * number_of_locations);
            auto row_end_iterator = dist_table.begin() + ((curr_node + 1) * number_of_locations);
            for (auto it = row_begin_iterator; it != row_end_iterator; ++it) {
                const auto index = std::distance(row_begin_iterator, it);
                if (!visited[index] && *it < min_dist)
                {
                    min_dist = *it;
                    min_id = index;
                }
            }
            visited[min_id] = true;
            curr_route.push_back(min_id);
            trip_dist += min_dist;
            curr_node = min_id;
        }

        // check round trip with this starting point is shorter than the shortest round trip found till now
        if (trip_dist < shortest_trip_distance) {
            shortest_trip_distance = trip_dist;
            route = curr_route;
        }
    }
    return route;
}

}
}
#endif // TSP_NEAREST_NEIGHBOUR_HPP