/// <summary>
/// Simulated Annealing, minimize the function.
/// </summary>
/// <param name="initial">Initial Solution.</param>
/// <param name="Temp0">Initial Temperature. (Temp0=1000)</param>
/// <param name="alpha">Update K. (alpha less than 1, alpha=.99)</param>
/// <param name="K0">Iterations Count each step (100).</param>
/// <param name="rho">Update K. (rho=1.05)</param>
/// <param name="A">Acceptations Count each step. (A=10)</param>
/// <param name="Frz">Final Temperature. (Frz=.5)</param>
/// <param name="iterationsCount">Iterations Count. (iterationsCount=1000)</param>
/// <param name="Neighbor">Delegate to calculate an Neighbor.</param>
/// <param name="parametersNeighbor">Neighbor's parameters.</param>
/// <param name="EvaluateSolution">Function to evaluate.</param>
/// <param name="parametersEvaluateSolution">EvaluateSolution's parameters.</param>ref int aMaxCluster
/// <param name="aMaxCluster">aMaxCluster the parameter to create new cluster in OneMoveElement.</param>
/// <returns>Best Solution.</returns>
public static string[] RunBOM(Set Set, string[] initial_sol, List <string[]> partitions, double Temp0, double alpha, double K0, double rho, double A, double Frz, double iterationsCount, IContainerProgressBar IContainerProgressBar, int _current, GenericDistances aGenericDistance, ref int aMaxCluster)
{
//string[] _result = initial_sol;
string[] _best = initial_sol;
double Temp = Temp0;
double K = K0;
double old_evaluation = 0;
double k = 0;
double a = 0;
double iteration = 0;
while (iteration < iterationsCount && A / K < Frz)
{
k = 0;
a = 0;
while (k < K && a < A)
{
old_evaluation = DelegateImplementations.S(Set, _best, partitions, aGenericDistance);
string[] nextSolution = DelegateImplementations.MoveOneElement(Set, _best, ref aMaxCluster);
double new_evaluation = DelegateImplementations.S(Set, nextSolution, partitions, aGenericDistance);
double diff = new_evaluation - old_evaluation;
if (diff < 0)
{
_best = nextSolution;
a++;
}
else
{
aMaxCluster = _best.Distinct <string>().Count();
}
k++;
}
//Update
Temp = alpha * Temp;
K = rho * K;
iteration++;
if (IContainerProgressBar != null)
{
IContainerProgressBar.UpdateProgressBar(_current++, "Running BOM algorithm...", false);
}
}
return(_best);
}
/// <summary>
/// Simulated Annealing, minimize the function.
/// </summary>
/// <param name="initial">Initial Solution.</param>
/// <param name="Temp0">Initial Temperature. (Temp0=1000)</param>
/// <param name="alpha">Update K. (alpha less than 1, alpha=.99)</param>
/// <param name="K0">Iterations Count each step (100).</param>
/// <param name="rho">Update K. (rho=1.05)</param>
/// <param name="A">Acceptations Count each step. (A=10)</param>
/// <param name="Frz">Final Temperature. (Frz=.5)</param>
/// <param name="iterationsCount">Iterations Count. (iterationsCount=1000)</param>
/// <param name="Neighbor">Delegate to calculate an Neighbor.</param>
/// <param name="parametersNeighbor">Neighbor's parameters.</param>
/// <param name="EvaluateSolution">Function to evaluate.</param>
/// <param name="parametersEvaluateSolution">EvaluateSolution's parameters.</param>ref int aMaxCluster
/// <param name="aMaxCluster">aMaxCluster the parameter to create new cluster in OneMoveElement.</param>
/// <returns>Best Solution.</returns>
public static string[] RunSAOMNewNeighbor(Set Set, string[] initial_sol, List <string[]> partitions, double Temp0, double alpha, double K0, double rho, double A, double Frz, double iterationsCount, IContainerProgressBar IContainerProgressBar, int _current, GenericDistances aGenericDistance, ref int aMaxCluster)
{
string[] _result = initial_sol;
string[] _best = _result;
double Temp = Temp0;
double K = K0;
double old_evaluation = 0;
double k = 0;
double a = 0;
double iteration = 0;
while (iteration < iterationsCount && A / K < Frz)
{
k = 0;
a = 0;
while (k < K && a < A)
{
old_evaluation = DelegateImplementations.S(Set, _best, partitions, aGenericDistance);
string[] nextSolution = DelegateImplementations.MeetJoinClusters(Set, _result, ref aMaxCluster);
double new_evaluation = DelegateImplementations.S(Set, nextSolution, partitions, aGenericDistance);
double diff = new_evaluation - old_evaluation;
if (diff < 0)
{
_best = nextSolution;
_result = nextSolution;
a++;
}
else
{
double r = new Random(Environment.TickCount).NextDouble();
if (r < Math.Exp(-diff / Temp))
{
_result = nextSolution;
a++;
}
else
{
aMaxCluster = _result.Distinct <string>().Count();
}
}
k++;
}
//Update
Temp = alpha * Temp;
K = rho * K;
iteration++;
if (IContainerProgressBar != null)
{
IContainerProgressBar.UpdateProgressBar(_current++, "Running SAOMNewNeighbor algorithm...", false);
}
}
return(_best);
}
