Hi,

I was using GLPK within JuMP to solve an integer linear program. The value of the decision variables are close to integer values. I can just round them if they are within an accepted tolerance.

However, GLPK optimizer has parameters for integer tolerance.

```
julia> opt = GLPK.Optimizer()
A GLPK model
julia> opt.intopt_param.tol_int
1.0e-5
```

```
ERROR: InexactError: Int64(-101.99999999999999)
Stacktrace:
[1] Int64
@ ./float.jl:812 [inlined]
[2] convert
@ ./number.jl:7 [inlined]
[3] _broadcast_getindex_evalf
@ ./broadcast.jl:670 [inlined]
[4] _broadcast_getindex
@ ./broadcast.jl:653 [inlined]
[5] getindex
@ ./broadcast.jl:597 [inlined]
[6] macro expansion
@ ./broadcast.jl:961 [inlined]
[7] macro expansion
@ ./simdloop.jl:77 [inlined]
[8] copyto!
@ ./broadcast.jl:960 [inlined]
[9] copyto!
@ ./broadcast.jl:913 [inlined]
[10] copy
@ ./broadcast.jl:885 [inlined]
[11] materialize
@ ./broadcast.jl:860 [inlined]
[12] ideal(problem::MOIntegerLinearProblem)
```

Is it possible to get JuMP to return integer values for these variables or rounding is necessary? Is this solver parameter merely used for integrality check?

Thanks