I’m completely new to mathematical optimisation and would appreciate if you could give a hint here.

I have a function of three vectors x, y and z(each of size 15). Now I want to maximise a function of the vectors with constraints:

```
function build_model()
model = Model(Ipopt.Optimizer)
@variable(model, x[i=1:n]);
@variable(model, y[i=1:n]);
@variable(model, z[i=1:n]);
@NLconstraint(model, sum(x[i] for i=1:n) <= cx)
@NLconstraint(model, sum(y[i] for i=1:n) <= cy)
@NLconstraint(model, sum(z[i] for i=1:n) <= cz)
@NLexpression(model, my_expr,
sum(
wx*((Ax[i] * x[i]^2) / (120 + x[i]^2 + 2y[i] - 0.8x[i] * z[i] + z[i]^2)) + wy*((Ay[i] * y[i]^2) / (30 + 4x[i] + y[i]^2 + 7z[i])) + wz*((Az[i] * z[i]^2) / (80 + 0.4x[i] + 0.2x[i]*z[i] +0.6y[i] + z[i]^2)) for i=1:n
)
)
@NLobjective(model, Max, my_expr)
return model
end
model = build_model();
optimize!(model)
termination_status(model)
```

wx, wy, wz and cx, cy, cz are some scalars. Ax, Ay, Az are arrays of size 15.

The result is `NUMERICAL_ERROR::TerminationStatusCode = 20`

Does the way I’m using JuMP make sense? How would go about debugging the issue?

Thanks in advance!