Example 1: Solving a general nonlinear programming problem

A general nonlinear programming problem is solved using a finite difference gradient. The problem

{\rm {min}} \,\, F(x) = (x_1 - 2)^2 + (x_2 - 1)^2

subject to

g_1(x) = x_1 - 2x_2 + 1 = 0

g_2(x) = -x_1^2 / 4 - x_2^2 + 1 \ge 0

is solved.

import com.imsl.math.*;

public class MinConNLPEx1 implements MinConNLP.Function{
    
    public double f(double[] x, int iact, boolean[] ierr){
        double result;
        ierr[0] = false;
        if(iact == 0){
            result = (x[0]-2.e0)*(x[0]-2.e0) + (x[1]-1.e0)*(x[1]-1.e0);
            return result;
        } else {
            switch (iact) {
                case 1:
                    result = (x[0]-2.e0*x[1] + 1.e0);
                    return result;
                case 2:
                    result = (-(x[0]*x[0])/4.e0 - (x[1]*x[1]) + 1.e0);
                    return result;
                default:
                    ierr[0] = true;
                    return 0.e0;
            }
        }
    }
    
    public static void main(String args[]) throws Exception {
        int     m = 2;
        int     me = 1;
        int     n = 2;
        double	xinit[] = {2., 2.};
        double  x[] = {0.};
        MinConNLP minconnon = new MinConNLP(m, me, n);
        minconnon.setGuess(xinit);
        MinConNLPEx1 fcn = new MinConNLPEx1();
        x = minconnon.solve(fcn);
        System.out.println("x is "+x[0] +" "+x[1]);
    }
}

Output

x is 0.8228756555325116 0.9114378277662559
Link to Java source.