Hi, I am working on an optimization problem as described in the PDF document in the GitHub repository. The nonlinearity is introduced mainly the equation `G`

in (16).

I implemented the model following closely the PDF description with JuMP. The code and example data are all provided in the GitHub repository. Since there is a nonlinear term in the objective (10), I chosen the `SCIP`

solver and also the `Alpine`

solver. Both reported the error below:

```
ERROR: MathOptInterface.UnsupportedAttribute{MathOptInterface.ObjectiveFunction{MathOptInterface.ScalarNonlinearFunction}}:
Attribute MathOptInterface.ObjectiveFunction{MathOptInterface.ScalarNonlinearFunction}() is not supported by the model.
```

After Googling, a suggestion is to replace the nonlinear term in the objective with an auxiliary variable (see `f_obj_aux`

in the code nlp.jl), and put that term into the constraints. However, I still got a similar error:

```
ERROR: MathOptInterface.UnsupportedConstraint{MathOptInterface.ScalarNonlinearFunction, MathOptInterface.LessThan{Float64}}: `MathOptInterface.ScalarNonlinearFunction`-in-`MathOptInterface.LessThan{Float64}` constraint is not supported by the model.
```

- Is it due to the solver? Perhaps there exists some solver capable of handling it.
- Shall I reformulate the problem to make it a better-posed one? But how. This problem may be probably turned into a recognized form but I donâ€™t know. I am no expert in optimization.

Any suggestion is appreciated.