(Julia beginner)

Still thinking about Nonlinear Programming with JuMP with some generality.

(@NLconstraint with a sum, array and scalar variables)

There are many NLP JuMP examples available but all more or less similar to the Rosenbrok problem in the sense that they involve a few explicit functions for objective and constraints.

My intuition for my own problem (pyro chemistry) is that I might need to create many nonlinear functions and that I would use as part of an array of functions or a dictionary of functions.

Therefore when registering some new function(s) with some symbol(s) like here:

`JuMP.register(model, :hJuMP, 1, hjulia; autodiff=true)`

there is the problem that I will probably never be able to use literally the `hJuMP`

symbol created in this statement. Instead, my likely use of `hJuMP`

would be as one element from a list of such function:

```
funlist = [..., ..., hJuMP, ..., ...]
@NLconstraint(model, funlist[idx](T, xs...) == h0)
```

This kind of statement does not work and return for example this error:

```
LoadError: MethodError: no method matching _is_sum(::Expr)
```

I tried several variant of the idea without success.

Would there be a way to use JuMP/Julia as above?

Or should I think otherwise?

Thanks for your suggestions,

Michel