I have a non-linear optimization problem to be solved with JuMP and IPOPT solver. The objective function is a probability distribution function of a normal distribution. It can be optimized by IPOPT directly, but not supported by JuMP. Is there any method to solve this problem? As the constrains are complicated, I hope to write constrains with JuMP. Thanks a lot !

The codes with error are as follows.

```
func1(x)=1/(2*3.1415926)^0.5/20*exp(-(x-100)^2/2/20^2)
gp = Model(with_optimizer(Ipopt.Optimizer))
@variable(gp, Q)
@objective(gp, Max, integrate(func1)(Q))
optimize!(gp)
```

ERROR: LoadError: The objective function `0.199471141902022*sqrt(2)*sqrt(pi)*erf(sqrt(2)*(x - 100)/40)`

is not supported by JuMP.