/// <summary>
/// Find vector x that minimizes the function f(x), constrained within bounds, using the Broyden–Fletcher–Goldfarb–Shanno Bounded (BFGS-B) algorithm.
/// The missing gradient is evaluated numerically (forward difference).
/// For more options and diagnostics consider to use <see cref="BfgsBMinimizer"/> directly.
/// </summary>
public static Vector <double> OfFunctionConstrained(Func <Vector <double>, double> function, Vector <double> lowerBound, Vector <double> upperBound, Vector <double> initialGuess, double gradientTolerance = 1e-5, double parameterTolerance = 1e-5, double functionProgressTolerance = 1e-5, int maxIterations = 1000)
{
var objective = ObjectiveFunction.Value(function);
var objectiveWithGradient = new Optimization.ObjectiveFunctions.ForwardDifferenceGradientObjectiveFunction(objective, lowerBound, upperBound);
var algorithm = new BfgsBMinimizer(gradientTolerance, parameterTolerance, functionProgressTolerance, maxIterations);
var result = algorithm.FindMinimum(objectiveWithGradient, lowerBound, upperBound, initialGuess);
return(result.MinimizingPoint);
}
public IObjectiveFunction CreateNew()
{
var tmp = new ForwardDifferenceGradientObjectiveFunction(this.InnerObjectiveFunction.CreateNew(), LowerBound, UpperBound, this.RelativeIncrement, this.MinimumIncrement);
return(tmp);
}
