Hi all,

I have a question regarding accessing infeasible optimization results.

For example, the following optimization does not have a feasible solution. However, despite the infeasibility, it is still able to give the value of x and y.

```
model = Model()
set_optimizer(model, GLPK.Optimizer)
@variable(model, x >= 6.0)
@variable(model, y >= 6.0)
@objective(model, Max, 2* x + y )
@constraint(model, x+y <= 11.0)
@constraint(model, x >= 1.0)
optimize!(model)
value.(x)
```

When there is a semicontinuous variable, it returns the following errors when I was trying to get the variable value.

```
model = Model()
set_optimizer(model, GLPK.Optimizer)
@variable(model, x in MOI.Semicontinuous(6.0, 12.0))
@variable(model, y >= 6.0)
@objective(model, Max, 2* x + y )
@constraint(model, x >= 1.0)
@constraint(model, x+y <= 11.0)
optimize!(model)
value.(y)
```

Can someone help me to understand why I am able to get â€ścomprisedâ€ť results when there is no feasible solution? However, when I use semicontinuous variables, I cannot get the value of those variables?

Thank you very much in advance.