//************************************
// Method: initPheromones
// FullName: CAntColonySystem::initPheromones
// Access: virtual public
// Returns: void
// Qualifier:
//************************************
void CAntColonySystem::initSystem()
{
double best_distance = (std::numeric_limits<double>::max)();
std::vector<size_t> randomPath = m_pLocalSearch->greedyPath(m_noNodes);
double dist=this->calculatePathLength(randomPath);
m_BestAntToDate.setAntsTour(randomPath);
if(m_LocalSearchOpt2)
m_pLocalSearch->opt2(m_BestAntToDate.getAntsCityTour());
else if(m_LocalSearchOpt3)
m_pLocalSearch->opt3(m_BestAntToDate.getAntsCityTour());
else if(m_LocalSearchGreed)
m_pLocalSearch->three_opt_first(randomPath , m_nnList);
m_BestAntToDate.setAntsTour(randomPath);
m_BestAntToDate.setAntTourLength(this->calculateAntPathLength(m_BestAntToDate));
tau0 = 1.0/ ((double)m_noNodes * dist);
for (size_t i=0; i<m_noNodes; i++)
{
for (size_t j=0; j< m_noNodes; j++)
this->m_newPheromoneMatrix->set(i, j , tau0);
}
//added
initAnts();
calculateHeuristicMatrix();
// clog.logMatrix(m_newPheromoneMatrix->getMatrix());
}
int simulateACO(){
static int iteration;
int max;
initAnts();
simulateAllTour();
}
int simulateACO(){
static int iteration;
int max;
initAnts();
simulateAllTour();
simulateAllPheromone();
max = finateIteration();
if(!parameterAdjustmentMode) printf("interation = %d\n", iteration);
iteration++;
return max;
}
//************************************
// Method: constructSolutions
// FullName: CAntColonySystem::constructSolutions
// Access: virtual public
// Returns: void
// Qualifier:
//************************************
void CAntColonySystem::constructSolutions()
{
m_tourTime.startTimer();
//clear ants memory and shuffle start pos
initAnts();
//place ants in ramdom citys for starting
for (size_t k = 0; k < m_Ants.size(); k++ )
{
m_Ants[k].setAntCity(0,m_randomPath[k]);
m_Ants[k].setCityVisited(m_randomPath[k]);
}
uniform_real<double> rndSelTrsh(0.0, 1.0);
uniform_real<double> m_ChoiceExplore(0.0 , 1.0);
for(size_t step = 1 ; step < m_noNodes; step++)
{
for(size_t k = 0; k < m_Ants.size(); k++)
{
decisionRule(k,step, rndSelTrsh, m_ChoiceExplore);
// localPheromoneUpdate(k,m_Ants[k].getCity(step));
}
}
for(size_t k = 0; k < m_Ants.size(); k++)
{
int tourstart=m_Ants[k].getCity(0);
m_Ants[k].setAntCity(m_noNodes,tourstart);
m_Ants[k].setAntTourLength((int)this->calculateAntPathLength(m_Ants[k]));
// size_t idx1 = this->m_Ants[k].getCity(m_noNodes);
// size_t idx2 = m_Ants[k].getCity(m_noNodes-1);
// m_newPheromoneMatrix->local_pheromone_update(m_noNodes-1, m_Ants[k].getAntsCityTour()[0] ,xi, tau0);
// localPheromoneEndIndexUpdate(idx1, idx2);
}
for(size_t k = 0; k < m_Ants.size(); k++)
for(size_t i=0;i<m_Ants[k].getAntsCityTour().size();i++)
{
if(i==0)
m_newPheromoneMatrix->local_pheromone_update(m_noNodes-1, m_Ants[k].getAntsCityTour()[i] ,xi, tau0);
else
m_newPheromoneMatrix->local_pheromone_update(m_Ants[k].getAntsCityTour()[i-1], m_Ants[k].getAntsCityTour()[i],xi , tau0 );
}
m_tourStats.tourAverageTime = (m_tourTime.getElapsedTime())/ (m_Ants.size()-1);
m_tourTime.stopTimer();
updateBestSoFarPath();
}
void simulateAllTour(){
initAnts();
for(int i = 0; i < swarmSize; i++){
simulateTour(i);
}
}
void initACO(WAY * way){
initWay(way);
if(!isAlloced) allocAnts();
initAnts();
printf("initialized\n");
}
void initACO(){
initTau();
if(!isAlloced) allocAnts();
initAnts();
printf("initialized\n");
}
