I am not sure if this is a JuMP or NLopt issue but whenever I try to do a loop with a NLP inside defining a parameter in each iteration, it only works if I am using a single thread.

For example, the code below does not work:

```
using JuMP, NLopt
model = Model(NLopt.Optimizer)
set_optimizer_attribute(model, "algorithm",:LD_MMA )
@variable(model, z)
@NLparameter(model, x == 1.0)
@NLobjective(model, Min, (z - x)^2)
A = rand(100)
Threads.@threads for x0 in A
set_value(x, x0)
JuMP.optimize!(model)
@show value(x)
end
```

While the code below works:

```
Threads.@threads for x0 in A
model = Model(NLopt.Optimizer)
set_optimizer_attribute(model, "algorithm",:LD_MMA )
@variable(model, z)
@NLparameter(model, x == x0)
@NLobjective(model, Min, (z - x)^2)
JuMP.optimize!(model)
@show value(x)
end
```

However, I believe the point of parameters is not having to define the whole model in each iteration.

The only other NLP solver I have is Ipopt with MUMPS which I believe cannot be multithreaded anyway.