Hello,

I’m still very new with Julia, and I’m having troubles with my MINLP optimization problem that I used to solve with MATLAB.

I can’t find a way to provide an user-defined objective function to the @NLobjective macro.

The problem is that my objective function cannot be defined (like in most examples) in an analytic way as a function of my variables.

Here’s a MWE (actually, in this particular case, I could have expressed myfunction in a row, but what I need is to do that with an “outer” function, as I did):

```
using JuMP,Ipopt,Cbc,Juniper
optimizer = Juniper.Optimizer
params = Dict{Symbol,Any}()
params[:nl_solver] = with_optimizer(Ipopt.Optimizer, print_level=0)
m = Model(with_optimizer(optimizer, params))
@variable(m, 0 <= x[1:4] <= 6, Int)
function myfunction(x1,x2,x3,x4)
xx=[x1,x2,x3,x4]
return sum(xx[i] for i = 1:4)
end
register(m, :myfunction, 4, myfunction; autodiff = true)
@NLobjective(m,Max,myfunction(x[1],x[2],x[3],x[4]))
print(m)
optimize!(m)
```

The problem that arises is:

KeyError: key :myfunction not found

Any help is really appreciated. Thanks a lot!