please, can you help me with my (probably very simple) problem? I wanted to solve a convex (quadratic) toy problem using the QCP solver. But, I realized that it doesn't work properly. In particular, it simply ignores the quadratic terms in the constraint (e.g. if I set the coefficient for x1 in the constraint to zero, there is no feasible solution).

Thank you very much for any help.

Frantisek

Code: Select all

```
FREE VARIABLES
OF objective function's value;
VARIABLE
x1 variable 1
x2 variable 2 ;
EQUATION
obj objective function
con constraint
bound_x1 non-negativity constraint for x1
bound_x2 non-negativity constraint for x2;
obj.. OF=e=1*x2+.01*power(x1,2);
con.. 0.01*x1+5*power(x2,2)=g=100;
bound_x1.. x1=g=0;
bound_x2.. x2=g=0;
MODEL nonlinear_problem /all/;
SOLVE nonlinear_problem USING QCP minimizing OF;
```