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.};

        MinConNLP minconnon = new MinConNLP(m, me, n);
        minconnon.setGuess(xinit);
        MinConNLPEx1 fcn = new MinConNLPEx1();
        double[] x = minconnon.solve(fcn);
        System.out.println("x is " + x[0] + " " + x[1]);
    }
}

Output

x is 0.8228756555325116 0.9114378277662559
Link to Java source.