Example 2: Solving a general nonlinear programming problem

subject to

is solved.

using System;
using Imsl.Math;

public class MinConNLPEx2 : MinConNLP.IGradient
{
    public double F(double[] x, int iact, bool[] ierr)
    {
        double result;
        ierr[0] = false;
        if (iact == 0)
        {
            result = (x[0] - 2.0) * (x[0] - 2.0) + 
                (x[1] - 1.0) * (x[1] - 1.0);
            return result;
        }
        else
        {
            switch (iact)
            {
                
                case 1: 
                    result = (x[0] - 2.0 * x[1] + 1.0);
                    return result;
                
                case 2: 
                    result = (-(x[0] * x[0]) / 4.0 - 
                        (x[1] * x[1]) + 1.0);
                    return result;
                
                default: 
                    ierr[0] = true;
                    return 0.0;
                
            }
        }
    }
    
    
    public void Gradient(double[] x, int iact, double[] result)
    {
        if (iact == 0)
        {
            result[0] = 2.0 * (x[0] - 2.0);
            result[1] = 2.0 * (x[1] - 1.0);
            return;
        }
        else
        {
            switch (iact)
            {
                case 1: 
                    result[0] = 1.0;
                    result[1] = - 2.0;
                    return;
                
                case 2: 
                    result[0] = - 0.5 * x[0];
                    result[1] = - 2.0 * x[1];
                    return;
                }
        }
    }
    

    public static void  Main(String[] args)
    {
        int m = 2;
        int me = 1;
        int n = 2;
        MinConNLP minconnon = new MinConNLP(m, me, n);
        minconnon.SetGuess(new double[]{2.0, 2.0});
        double[] x = minconnon.Solve(new MinConNLPEx2());
        new PrintMatrix("x").Print(x);
    }
}

Output

          x
           0          
0  0.822875655532512  
1  0.911437827766256