/// <summary>
/// Solve the quadratic programming optimization problem using the Goldfarb-Idnani dual method
/// </summary>
/// <param name="Dmat"></param>
/// <param name="dvec"></param>
/// <param name="Amat"></param>
/// <param name="bvec"></param>
/// <param name="meq"></param>
/// <param name="factorized"></param>
/// <returns></returns>
public static OptimizationResult Solve(MathLib.Matrix <double> Dmat, double[] dvec, MathLib.Matrix <double> Amat, double[] bvec, int meq = 0, bool factorized = false)
{
//PerformanceLogger.Start("QuadProg", "Solve", "Initialize");
Initialize();
//PerformanceLogger.Stop("QuadProg", "Solve", "Initialize");
DenseVector vec;
if (dvec == null)
{
vec = new DenseVector(Dmat.ColumnCount, 0);
}
else
{
vec = new DenseVector(dvec);
}
//PerformanceLogger.Start("QuadProg", "Solve", "R.CallFunction");
Engine.SetSymbol("result", Engine.CallFunction("solve.QP", Engine.RMatrix(Dmat.ToArray()),
Engine.RVector(vec.ToArray()), Engine.RMatrix(Amat.ToArray()),
Engine.RVector(bvec), Engine.RNumeric(meq), Engine.RBool(factorized)));
var sol = Engine.RunCommand("result$solution").AsNumeric().ToArray <double>();
var val = Engine.RunCommand("result$value").AsNumeric().ToArray <double>().First();
//PerformanceLogger.Stop("QuadProg", "Solve", "R.CallFunction");
return(new OptimizationResult(sol, val * 2));
}
/// <summary>
/// Quadratic programming optimization solver using the dual method algorithm of Goldfarb and Idnani
/// </summary>
/// <param name="Dmat"></param>
/// <param name="dvec"></param>
/// <param name="Amat"></param>
/// <param name="bvec"></param>
/// <param name="meq"></param>
public static OptimizationResult Solve(MathLib.Matrix <double> Dmat, double[] dvec, MathLib.Matrix <double> Amat, double[] bvec, int meq = 0, bool factorized = false)
{
// return optim = optim, weights= weights, targetReturn = bvec[1], targetRisk = sqrt(weights*Dmat*weights)[[1,1]]
var target = new GoldfarbIdnaniQuadraticSolver(Dmat.RowCount, Amat.ToArray(), bvec, meq);
var min = target.Minimize(Dmat.ToArray(), dvec);
var sol = target.Solution;
return(new OptimizationResult(sol, min * 2));
}