/// <summary>
/// Finds the minimum value of a function. The solution vector
/// will be made available at the <see cref="IOptimizationMethod{TInput, TOutput}.Solution" /> property.
/// </summary>
/// <returns>
/// Returns <c>true</c> if the method converged to a <see cref="IOptimizationMethod{TInput, TOutput}.Solution" />.
/// In this case, the found value will also be available at the
/// <see cref="IOptimizationMethod{TInput, TOutput}.Value" />
/// property.
/// </returns>
public override bool Minimize()
{
if (Gradient is null)
{
Gradient = FiniteDifferences.Gradient(Function, NumberOfVariables);
}
NonlinearObjectiveFunction.CheckGradient(Gradient, Solution);
return(base.Minimize());
}
/// <summary>
/// Finds the maximum value of a function. The solution vector
/// will be made available at the <see cref="IOptimizationMethod{TInput, TOutput}.Solution" /> property.
/// </summary>
/// <returns>
/// Returns <c>true</c> if the method converged to a <see cref="IOptimizationMethod{TInput, TOutput}.Solution" />.
/// In this case, the found value will also be available at the
/// <see cref="IOptimizationMethod{TInput, TOutput}.Value" />
/// property.
/// </returns>
public override bool Maximize()
{
if (Gradient is null)
{
Gradient = FiniteDifferences.Gradient(Function, NumberOfVariables);
}
NonlinearObjectiveFunction.CheckGradient(Gradient, Solution);
var g = Gradient;
Gradient = x => g(x).Multiply(-1);
var success = base.Maximize();
Gradient = g;
return(success);
}