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.
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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;