Example 2: Solving a general nonlinear programming problem
A general nonlinear programming problem is solved using a user-supplied gradient.
import com.imsl.math.*;
public class MinConNLPEx2 implements MinConNLP.Gradient{
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 void gradient(double[] x, int iact, double[] result){
if(iact == 0){
result[0] = 2.e0*(x[0]-2.e0);
result[1] = 2.e0*(x[1]-1.e0);
return;
} else {
switch (iact) {
case 1:
result[0] = 1.e0;
result[1] = -2.e0;
return;
case 2:
result[0] = -0.5e0*x[0];
result[1] = -2.e0*x[1];
return;
}
}
}
public static void main(String args[]) throws Exception {
int m = 2;
int me = 1;
int n = 2;
MinConNLP minconnon = new MinConNLP(m, me, n);
minconnon.setGuess(new double[]{2.,2.});
MinConNLPEx2 grad = new MinConNLPEx2();
double x[] = minconnon.solve(grad);
System.out.println("x is "+x[0] +" "+x[1]);
}
}
Output
x is 0.8228756555325117 0.9114378277662558
Link to Java source.