public QuasiNewtonMethod(double eps, Vector startVector)
{
StartVector = startVector;
epsilon = eps;
currentValue = startVector;
int n = startVector.GetVectorSize;
hessianMatrix = new Matrix(n, n).IdentityMatrix();
}
public MethodResult Execute(FunctionDelegate F, GradientDelegate Gradient, OptimizationMethod OptimizationMethod, int MaxIterations)
{
stopwatch.Start();
for (int i = 0; i < MaxIterations; i++)
{
var oldGradientValue = Gradient(currentValue);
Vector newDirection = -(hessianMatrix * oldGradientValue);
var lambda = OptimizationMethod((alpha) => { return F(currentValue + alpha * newDirection); }, -10, 10, 1E-9, MaxIterations);
var vector = lambda * newDirection;
currentValue = vector + currentValue;
//var functionValue = F(currentValue);
var gradientValue = Gradient(currentValue);
if (gradientValue.LengthSquared < epsilon || vector.LengthSquared < epsilon)
{
stopwatch.Stop();
return new MethodResult() { Result = new Vector[] { currentValue }, IterationEnd = false, MethodName = "Квазиньютоновский метод", Iterations = i, stopwatch = stopwatch, StartPoint = new Vector[] { StartVector }, FunctionValue = F(currentValue) };
}
var matrixU = gradientValue - oldGradientValue;
var matrixA = (vector * vector.GetTranspose()) / (vector.ToMatrix().GetTranspose() * matrixU)[0, 0];
var matrixB = -(hessianMatrix * matrixU * matrixU.GetTranspose() * hessianMatrix) / (matrixU.GetTranspose() * hessianMatrix * matrixU)[0, 0];
hessianMatrix = hessianMatrix + matrixA + matrixB;
}
return new MethodResult() { Result = new Vector[] { currentValue }, IterationEnd = true, MethodName = "Квазиньютоновский метод", Iterations = MaxIterations, stopwatch = stopwatch, StartPoint = new Vector[] { StartVector }, FunctionValue = F(currentValue) };
}
