public ISolution NextPos()
{
// calculated using Euclidean Distance
if (old == null)
{
InitPos();
}
// Calc gradient
var grad = Grad(d0, d, old);
// - grad * alpha
foreach (var pt in grad)
{
pt[0] = -pt[0] * Alpha; // X
pt[1] = -pt[1] * Alpha; // Y
}
// next_step = old - alpha * grad
for (int k = 0; k < n; k++)
{
grad[k][0] += old.GetArgument()[k][0]; // X
grad[k][1] += old.GetArgument()[k][1]; // Y
}
// save changes and return
d = MDS.CalcDistances(grad, MDS.EuclideanDistance);
old = new Solution(fun, d0, d, n, grad);
return(old);
}
public ISolution InitPos()
{
// random solution for start
Random r = new Random();
List <double[]> pts = new List <double[]>();
for (int k = 0; k < n; k++)
{
pts.Add(new double[2] {
RndRange(r, min, max), RndRange(r, min, max)
});
}
d = MDS.CalcDistances(pts, MDS.EuclideanDistance);
old = new Solution(fun, d0, d, n, pts);
return(old);
}
private ISolution NewSolution()
{
const double min = -1;
const double max = 1;
Random r = new Random();
var y = new List <double[]>();
for (int j = 0; j < count; j++)
{
double[] _y = new double[dimY];
for (int i = 0; i < dimY; i++)
{
_y[i] = NextGaussian(r, 1, 1) * (Math.Abs(min) + Math.Abs(max)) + min; // r.NextDouble()
}
y.Add(_y);
}
return(new Solution(MDS.KruskalStress, d0, MDS.CalcDistances(y, MDS.EuclideanDistance), count, y));
}
