public async void MOGA_FitnessEvaluation(int[] token)
{
List <Task> lTasks = new List <Task>();
int remainTasks = tempPool.Count;
// Test inputs Generation
// Fitness Evaluation
for (int k = 0; k < tempPool.Count; k++)
{
//Console.WriteLine("{0}'th genotype fitness assement", k);
GAEncoding ga = tempPool.ElementAt(k).Key;
//// Single Thread
//var tmpTuple = ga.CalEstFitness(enVar);
//tempPool[ga][0] = tmpTuple.Item1;
//ga.SetCEFitness(tmpTuple.Item2.ToArray());
lTasks.Add(Task.Run(() =>
{
ga.CalEstFitness(enVar);
// Console.WriteLine("{0}'th finished assement", k);
}));
if (lTasks.Count == 8 || (tempPool.Count - k - 1 < 8))
{
for (int i = 0; i < lTasks.Count; i++)
{
await lTasks[i];
}
lTasks.Clear();
}
}
token[0] = 1;
//Console.WriteLine("Fitness Evaluation Done");
}
private void MOGA_Initialization()
{
//CEPool cePool = null;
//CEPool tempPool = null;
// public CEPool ceFitness = null;
cePool = new CEPool();
tempPool = new CEPool();
for (int i = 0; i < popSize; i++)
{
var newSolution = new GAEncoding(pNumOfParams, dimension, enVar);
newSolution.FixInputs(enVar);
tempPool.Add(newSolution, new double[] { -1, -1 });
}
}
// Recombination: create a new solution, call this function;
// Add the new solution to the population
internal GAEncoding PanmicticRecomb(CEPool currentPool, int[] selectedList)
{
// Select solution to combine
// Find Average
Matrix <double> avgWeight = Matrix.Build.Dense(_numOfParams + 1, _dimension);
for (int i = 0; i < selectedList.Length; i++)
{
avgWeight += currentPool.ElementAt(selectedList[i]).Key.weights;
}
avgWeight = avgWeight / selectedList.Length;
// ... Check the sum of each row should be equal to a constant max
GAEncoding newSolution = new GAEncoding(_numOfParams, _dimension, _enVar);
newSolution.FixInputs(_enVar);
newSolution.weights = avgWeight;
return(newSolution);
}
public List <string> Print_Solution(GAEncoding solution)
{
string theta = null;
string weight = null;
for (int i = 0; i < solution.thetaDelta.RowCount; i++)
{
string tmp = "(";
Vector <double> vTemp = solution.thetaDelta.Row(i);
for (int j = 0; j < dimension; j++)
{
tmp = tmp + Math.Round(vTemp[j], 2) + " ";
}
tmp.Remove(tmp.Length - 1, 1);
tmp = tmp + ")";
theta = theta + tmp + " ";
}
theta.Remove(theta.Length - 1, 1);
for (int i = 0; i < solution.weights.RowCount; i++)
{
string tmp = "[";
Vector <double> vTemp = solution.weights.Row(i);
for (int j = 0; j < dimension; j++)
{
tmp = tmp + Math.Round(vTemp[j], 2) + " ";
}
tmp.Remove(tmp.Length - 1, 1);
tmp = tmp + "]";
weight = weight + tmp + " ";
}
weight.Remove(weight.Length - 1, 1);
return(new List <string>()
{
theta, weight
});
}
