Hello,

I’m solving a linear optimization problem with JuMP (0.19.2) using GLPK.jl (0.10.0) as the solver. I’m struggling with the situation where the lower and upper bounds of a variable are equal (and because it’s in a vector of inequalities, I can’t just simply remove the variable). Here is a MWE:

```
using JuMP #Call the modeling language
using GLPK # Call the solver
probm = Model(with_optimizer(GLPK.Optimizer,))
@variable(probm, x[1:2])
xmax = [10., 0.]
@constraint(probm, 0. .<= x .<= xmax)
@objective(probm, Min, 0)
optimize!(probm)
```

The output is:

```
glp_simplex: row 2: lb = 0, ub = 0; incorrect bounds
```

I found related discussion on GLPK mailing list, and a slightly similar thread here but with Ipopt. However, I wonder if it’s possible to use GLPK here (with Clp it works). Maybe it’s possible to switch to using GLPK’s interior point solver, but I don’t know how. And maybe someone would have a better trick! Thanks for your help!