bool Weighted_graph::is_connected() const {
// if empty graph with no vertex, return "unconnected"/false
if (vertex_num == 0) {
return false;
}
else {
minimum_spanning_tree(0);
}
// Iterate through MST_node_visited
// to see if it connects all the nodes
// If not, return false; otherwise, return true
for (int i = 0; i < vertex_num; ++i) {
if (!MST_node_visited[i]) {
return false;
}
}
return true;
}
std::list<index_t> mst_heuristic::build_solution(tsp_sym& instance){
// Using the symmetric problem derived from the general one.
undirected_graph<distance_t> graph (instance.get_matrix());
// Getting minimum spanning tree of associated graph under the form
// of an adjacency list.
std::unordered_map<index_t, std::list<index_t>> adjacency_list
= minimum_spanning_tree(graph).get_adjacency_list();
// Initializing the depth-first search of the minimum spanning tree
// with any vertex. Using the list as a stack.
std::list<index_t> df_list;
index_t current_vertex = adjacency_list.begin()->first;
df_list.push_back(current_vertex);
std::list<index_t> tour;
while(!df_list.empty()){
current_vertex = df_list.back();
df_list.pop_back();
for(auto vertex = adjacency_list[current_vertex].cbegin();
vertex != adjacency_list[current_vertex].cend();
++vertex){
// Adding neighbour for further visit.
df_list.push_back(*vertex);
// Making sure current edge won't be used backward later.
adjacency_list[*vertex].remove(current_vertex);
}
tour.push_back(current_vertex);
}
return tour;
}
