I wish to implement Wolfe’s example

```
x0 = [0; 0.25; 0.0]
lb = [0.0; 0.0; 0.0]
ub = [Inf; Inf; 2.0]
@variable(nlp, lb[i] <= x[i = 1:3] <= ub[i], start = x0[i])
@NLobjective(
nlp,
Min,
4/3*(x[1]^2 - x[1] * x[2] + x[2]^2)^(3/4) - x[3]
)
```

The gradient is not defined at x[1]=x[2]=0.0 but one may fill the hole by forcing it to be [0,0,-1], which is the right value when evaluating the limit.

How may I force JuMP to return [0,0,1] instead of [NaN,NaN,1]

Thx,

vepiteski