How to handle NaNs?

Example:
```julia
julia> model = CUTEstModel("BENNETT5LS")
Minimization problem BENNETT5LS
nvar = 3, ncon = 0 (0 linear)

julia> x = model.meta.x0
3-element Array{Float64,1}:
-2000.0
50.0
0.8

julia> g = grad(model, x)
3-element Array{Float64,1}:
37.195399822788076
1518.022256935859
-478331.78119128384

julia> x1 = x - g
3-element Array{Float64,1}:
-2037.195399822788
-1468.022256935859
478332.5811912838

julia> obj(model, x1)
NaN
```
Solvers should be able to trap NaNs and return an appropriate status.