void Simulated_Annealing::cooling()
{
//Setting up initial temperature.
T = current_best_solution.first.size() * 10000;
do {
for (int i = 0; i < cooling_schedule; i++) {
//Getting new solution in the neighborhood.
candidate = newSolution(current_best_solution);
//If the new solution is better than our current best solution, this new solution becomes our current best solution.
//Otherwise, we eval new solution using metropolis step. If metropolis step returns true, the new solution becomes
//the current best solution.
if (current_best_solution.second >= candidate.second) {
current_best_solution = candidate;
}
else if(metropolisStep(current_best_solution.second, candidate.second)){
current_best_solution = candidate;
}
//If our current best solution is better than the historical better solution, it becomes the new historical best solution.
if (current_best_solution.second <= historical_best_solution.second)
historical_best_solution = current_best_solution;
}
//Cooling temperature.
T *= 0.90;
} while (T > 0.1);
}
/******************************************* sweep ******************************************/
void Simulation::sweep()
{
/*int i;
int N1 = N/2; //number of Metropolis steps before Wolff step
int N2 = N - N1; //number of Metropolis steps after Wolff step
for( i=0; i<N1; i++ )
{ metropolisStep(); }
if( lambda==1 )
{ wolffStep(); }
for( i=0; i<N2; i++ )
{ metropolisStep(); }*/
for( int i=0; i<N; i++ )
{ metropolisStep(); }
}
