int main( void ){
Timer T(true);
int final_nodes_num, edge_addition_num;
final_nodes_num = 30000;
edge_addition_num = 7;
ListGraph mGr;
lemon::Random mRandom;
mRandom.seedFromTime();
vector<int> nodeChoice;
set<int> mRndNodes;
vector<int> targets(edge_addition_num, -1);
int currentIndex = 0;
// First targets are all nodes
for(auto &v : targets){
v = currentIndex++;
mGr.addNode();
}
while (countNodes(mGr)<final_nodes_num ) {
// Add new node and connect to targets
currentIndex = mGr.id( mGr.addNode() );
for(const auto &v : targets ){
mGr.addEdge( mGr.nodeFromId( currentIndex ), mGr.nodeFromId( v ) );
}
// Add the nodes, which were connented again
nodeChoice.insert(nodeChoice.end(), targets.begin(), targets.end() );
nodeChoice.insert(nodeChoice.end(), edge_addition_num, currentIndex);
mRndNodes.clear();
while (mRndNodes.size() < edge_addition_num) {
mRndNodes.insert( nodeChoice[ mRandom.integer( nodeChoice.size() ) ] );
}
targets.clear();
targets.insert(targets.begin(), mRndNodes.begin(), mRndNodes.end() );
}
cout << "time: " << T.realTime() << endl;
cout << countNodes( mGr) << endl;
cout << countEdges( mGr) << endl;
graphWriter( mGr, "/Users/sonneundasche/Documents/FLI/DATA/05 LEMON Graphs/BaraBasiTEST.txt")
.run();
InDegMap<ListGraph> inDeg(mGr);
graphWriter( mGr, "/Users/sonneundasche/Documents/FLI/DATA/05 LEMON Graphs/BaraBasi_Degree_TEST.txt")
.nodeMap("degree", inDeg)
.skipEdges()
.run();
}
int main( void ){
Timer T(true);
int init_nodes_num, final_nodes_num, edge_addition_num;
init_nodes_num = 10;
final_nodes_num = 50;
edge_addition_num = 7;
typedef ListEdgeSet< ListGraph > EdgeSet;
ListGraph mListGraph;
EdgeSet mNewEdges( mListGraph );
FullGraph fg(init_nodes_num);
GraphCopy<FullGraph, ListGraph> cg( fg, mListGraph); // Create the seed nodes
cg.run();
int mNumEdges = countEdges( mListGraph );
EdgeSet::Edge e;
lemon::Random mRandom;
mRandom.seedFromTime();
ListGraph::Node newNode, randNode;
// new edges will be saved seperatly in an EdgeSet, not to change the original node degrees
for ( int i = init_nodes_num; i < final_nodes_num; i++){
mNumEdges = countEdges( mListGraph );
mNewEdges.clear();
newNode = mListGraph.addNode();
while ( countEdges( mNewEdges ) != edge_addition_num ) {
randNode = mListGraph.nodeFromId( mRandom[ mListGraph.maxNodeId() ] ) ;
// --- CALCULATE THE PROBABILITY
if ( mRandom.real() < (( (double)(countIncEdges(mListGraph, randNode)) / (double)( 2*mNumEdges ) )) ){
if ( findEdge( mNewEdges, newNode, randNode ) == INVALID){ // does the edge already exist?
mNewEdges.addEdge( newNode, randNode );
}
}
}
// Create the new edges in the original graph
for (EdgeSet::EdgeIt e( mNewEdges ); e!=INVALID; ++e){
mListGraph.addEdge( mNewEdges.u( e ), mNewEdges.v(e) );
}
}
cout << T.realTime() << endl;
cout << countEdges( mListGraph) << endl;
cout << countEdges( fg ) << endl;
}
// ATENÇÃO: Não modifique a assinatura deste método.
bool brach_and_bound999999(TSP_Data_R &tsp, const vector<DNode> &terminais, const vector<DNode> &postos,
const DNode source,
int delta, int maxTime, vector<DNode> &sol, double &lbound){
// Converte o TSP direcionado para um nao direcionado com duas arestas
ListGraph graph;
EdgeValueMap weights(graph);
// Adiciona os nos
for (ListDigraph::NodeIt u(tsp.g); u!=INVALID; ++u)
{
Node v = graph.addNode();
}
// Adiciona as arestas
for (ListDigraph::ArcIt ait(tsp.g); ait!=INVALID; ++ait)
{
// pega os dois nos incidentes
Arc a(ait);
DNode u = tsp.g.source(a);
DNode v = tsp.g.target(a);
// cria a mesma aresta no grafo não direcionado
Node gu = graph.nodeFromId(tsp.g.id(u));
Node gv = graph.nodeFromId(tsp.g.id(v));
// insere a aresta no grafo nao direcionado
Edge e = graph.addEdge(gu, gv);
// Atribui pesos as arestas
weights[e] = tsp.weight[a];
}
NodeStringMap nodename(graph);
NodePosMap posicaox(graph);
NodePosMap posicaoy(graph);
TSP_Data utsp(graph, nodename, posicaox, posicaoy, weights);
// utiliza o convertido
ListGraph::EdgeMap<GRBVar> x(graph);
GRBEnv env = GRBEnv();
GRBModel model = GRBModel(env);
// TODO: [Opcional] Comente a linha abaixo caso não queira inserir cortes durante a execução do B&B
model.getEnv().set(GRB_IntParam_LazyConstraints, 1);
model.getEnv().set(GRB_IntParam_Seed, 0);
model.set(GRB_StringAttr_ModelName, "TSPR - TSP with Refueling"); // name to the problem
model.set(GRB_IntAttr_ModelSense, GRB_MINIMIZE); // is a minimization problem
// Add one binary variable for each arc and also sets its cost in the objective function
for (EdgeIt e(utsp.g); e!=INVALID; ++e) {
char name[100];
Edge edge(e);
unsigned uid = utsp.g.id(utsp.g.u(edge));
unsigned vid = utsp.g.id(utsp.g.v(edge));
sprintf(name,"x_%s_%s",tsp.vname[tsp.g.nodeFromId(uid)].c_str(),tsp.vname[tsp.g.nodeFromId(vid)].c_str());
x[e] = model.addVar(0.0, 1.0, utsp.weight[e],GRB_BINARY,name);
}
model.update(); // run update to use model inserted variables
// converte os terminais e os postos
vector<Node> uterminais;
for (auto t : terminais)
{
unsigned tid = tsp.g.id(t);
uterminais.push_back(utsp.g.nodeFromId(tid));
}
NodeBoolMap upostos(utsp.g, false);
for (auto p: postos)
{
unsigned pid = tsp.g.id(p);
// upostos.push_back(utsp.g.nodeFromId(pid));
upostos[utsp.g.nodeFromId(pid)] = true;
}
// Adicione restrições abaixo
// (1) Nós terminais devem ser visitados exatamente uma vez
for (auto v : uterminais) {
GRBLinExpr expr = 0;
for (IncEdgeIt e(utsp.g,v); e!=INVALID; ++e){
expr += x[e];
}
model.addConstr(expr == 2 );
}
// (3) Nó source sempre presente no início do caminho
Node usource = utsp.g.nodeFromId(tsp.g.id(source));
GRBLinExpr expr = 0;
for (IncEdgeIt e(utsp.g,usource); e!=INVALID; ++e){
expr += x[e];
}
model.addConstr(expr >= 1 );
try {
model.update(); // Process any pending model modifications.
//if (maxTime >= 0) model.getEnv().set(GRB_DoubleParam_TimeLimit,maxTime);
subtourelim cb = subtourelim(utsp , x, usource, upostos, delta);
model.setCallback(&cb);
// TODO: [Opcional] Pode-se utilizar o valor de uma solução heurística p/ acelerar o algoritmo B&B (cutoff value).
//cutoff = tsp.BestCircuitValue-MY_EPS;
double cutoff = 0.0;
if (cutoff > MY_EPS) model.getEnv().set(GRB_DoubleParam_Cutoff, cutoff );
model.update(); // Process any pending model modifications.
model.optimize();
// Obtém o status da otimização
int status = model.get(GRB_IntAttr_Status);
if(status == GRB_INFEASIBLE || status == GRB_INF_OR_UNBD){
cout << "Modelo inviavel ou unbounded." << endl;
return false;
}
// Limitante inferior e superior do modelo
//lbound = model.get(GRB_DoubleAttr_ObjBoundC);
if( model.get(GRB_IntAttr_SolCount) <= 0 ){
cout << "Modelo nao encontrou nenhuma solucao viavel no tempo. LowerBound = " << lbound << endl;
return false;
}
else if (status == GRB_OPTIMAL){
if(verbose) cout << "O modelo foi resolvido ate a otimalidade." << endl;
}
else {
if(verbose) cout << "O modelo encontrou uma solucao sub-otima (i.e. nao ha garantia de otimalidade)." << endl;
}
double custo_solucao = model.get(GRB_DoubleAttr_ObjVal);
int uncovered=0;
EdgeBoolMap cover(utsp.g, false);
for (EdgeIt e(utsp.g); e!=INVALID; ++e)
{
if (BinaryIsOne(x[e].get(GRB_DoubleAttr_X)))
{
cover[e] = true;
uncovered++;
}
}
sol.push_back(tsp.g.nodeFromId(utsp.g.id(usource)));
convertSol(x, sol, tsp, utsp, usource, cover, uncovered);
// Calculo manual do custo da solução (deve ser igual ao ObjVal do Gurobi).
double soma=0.0;
ArcName aname(tsp.g);
vector<Arc> edgesSol;
ArcColorMap acolor(tsp.g);
// if( verbose ) cout << "####### " << endl << "Edges of Solution (B&B):" << endl;
// for (EdgeIt e(utsp.g); e!=INVALID; ++e){
// if (BinaryIsOne(x[e].get(GRB_DoubleAttr_X))){ // Note que se este método serve para variáveis binárias, p/ inteiras terá de usar outro método.
// soma += utsp.weight[e];
// edgesSol.push_back(tsp.g.arcFromId(utsp.g.id(e)));
// if( verbose) cout << "(" << tsp.vname[tsp.g.nodeFromId(utsp.g.id(utsp.g.u(e)))] << "," << tsp.vname[tsp.g.nodeFromId(utsp.g.id(utsp.g.v(e)))] << ")" << endl;
// acolor[tsp.g.arcFromId(utsp.g.id(e))] = BLUE;
// }
// }
// if( verbose ) cout << "####### " << endl;
if( verbose ) cout << "####### " << endl << "Edges of Solution (B&B):" << endl;
DNode u = sol[0];
for (int i=1; i<sol.size(); i++)
{
DNode v = sol[i];
soma += tsp.AdjMatD.Cost(u,v);
if ( verbose ) cout << "(" << tsp.vname[u] << "," << tsp.vname[v] << ")" << endl;
u = v;
}
if( verbose ) cout << "####### " << endl;
if( verbose ) cout << "Custo calculado pelo B&B = "<< soma << " / " << custo_solucao << endl;
if( verbose ){
cout << "Caminho encontrado a partir do vértice de origem (" << tsp.vname[source] << "): ";
for(auto node : sol){
cout << tsp.vname[node] << " ";
} // Obs: O caminho é gerado a partir do nó source, se o conjunto de arestas retornado pelo B&B for desconexo, o caminho retornado por 'path_search' será incompleto.
cout << endl << "Custo calculado da solucao (caminho a partir do no origem) = " << solutionCost(tsp, sol) << endl;
ostringstream out;
out << "TSP with Refueling B&B, cost= " << custo_solucao;
ViewListDigraph(tsp.g, tsp.vname, tsp.posx, tsp.posy, tsp.vcolor, acolor, out.str());
}
return true;
}
catch(GRBException e) {
cerr << "Gurobi exception has been thrown." << endl;
cerr << "Error code = " << e.getErrorCode() << endl;
cerr << e.getMessage();
}
catch (...) {
cout << "Model is infeasible" << endl;
return false;
}
return false;
}