Dear All, one year ago I have written a small note on how to use Julia from R through the ‘JuliaCall’ package. I wanted to update this page and encountered some problems with Julia’s JuMP package.

See Notes on JuliaCall at https://hwborchers.github.io/.

The problem I wanted to solve is minimizing the (generalized) Rosenbrock funtion with constraints `0.0 <= x_i`

and `sum(x)==1`

. Rosenbrock is defined as

```
function rosen(x...)
n = length(x); s = 0.0
for i = 1:length(x)-1
s += 100*(x[i+1] - x[i]^2)^2 + (x[i] - 1)^2
end
return s
end
```

Here is the version for minimizing Rosenbrock (with constraints `0.0<=x_i<=0.5`

only) that was correct last year:

```
01 using JuMP, Ipopt
02 m = Model(solver = IpoptSolver());
03 @variable(m, 0.0 <= x[1:10] <= 0.5);
04 for i in 1:10 setvalue(x[i], 0.1); end;
05 JuMP.register(m, :rosen, 10, rosen, autodiff=true);
06 JuMP.setNLobjective(m, :Min,
07 Expr(:call, :rosen, [x[i] for i=1:10]...));
08 sol = solve(m);
09 getvalue(x)
## [1] 0.5000000000 0.2630659929 0.0800311191 0.0165742352 0.0103806763
## [6] 0.0102120052 0.0102084109 0.0102042121 0.0100040851 0.0001000822
```

Please note that lines (5-7) have been suggested to me when I asked for help here on the Julia discussion forum.

I have learned by now that I have to make the following changes:

(2) Replace the solver in the Model call with “Model(Ipopt.Optimizer)”

(8) Replace “solve” with “optimize!”

(9) Replace “getvalue(x)” with “JuMP.value.(x)”

It is still unclear to me, and I tried to find something in the documentation:

(5) Do I still need to register the rosen function?

(*) Do I need to set the @NLexpression ?

(6) How to set a nonlinear objective function (with setNLobjective)?

If I can get this example right, I think I can do the rest of my applications alone. Of course, a link to proper documentation pages will also be helpful.

Many thanks.