public double[] Solve(
Func <double[], double> f,
double[] startValue,
int nIter)
{
OptVector xOld = new OptVector(startValue);
OptVector xNew = new OptVector();
OptVector derivativeOld = new OptVector(numericalDerivative.EvaluatePartialDerivative(f, xOld.MinArray, 1));
OptVector[] oldInvHessian = OptimizationHelper.GetIdentity(startValue.Length);
OptVector direction = OptVector.Mult(oldInvHessian, -1.0 * derivativeOld);
OptVector derivativeNew = new OptVector();
for (int i = 0; i < nIter; i++)
{
StepSize = strongWolfeLineSearch.GetStepLength(f, direction, xOld, 4.0, MaxIterLineSearch);
OptVector sk = StepSize * direction;
xNew = xOld + sk;
if (xNew.MinArray.Contains(double.NaN))
{
break;
}
if (EarlyExit &&
CheckEarlyExit(xNew, xOld))
{
break;
}
derivativeNew = new OptVector(numericalDerivative.EvaluatePartialDerivative(f, xNew.MinArray, 1));
OptVector yk = sk;
OptVector[] newInvHessian = GetApproximateInverseHessianMatrix(
oldInvHessian,
yk,
sk);
direction = OptVector.Mult(newInvHessian, derivativeNew) * -1.0;
xOld = xNew;
oldInvHessian = newInvHessian;
derivativeOld = derivativeNew;
}
return(xNew.MinArray);
}
private OptVector[] GetApproximateInverseHessianMatrix(
OptVector[] invHessian,
OptVector yk,
OptVector sk)
{
double denom = yk * sk;
OptVector[] skyk = OptVector.Mult(sk, yk);
OptVector[] yksk = OptVector.Mult(yk, sk);
OptVector[] sksk = OptVector.Mult(sk, sk);
OptVector[] v1 = OptVector.SubtractFromIdentity(OptVector.Div(skyk, denom));
OptVector[] v2 = OptVector.SubtractFromIdentity(OptVector.Div(yksk, denom));
OptVector[] v3 = OptVector.Div(sksk, denom);
return(OptVector.Sum(OptVector.Mult(OptVector.Mult(v1, invHessian), v2), v3));
}
