Thank you, however I've read those very sections thoroughly, and as far as I can tell adding QP variables is distinct from adding linear integer variables. There is no clear explanation of how to force QP variables to be integers.
On Saturday, January 17, 2015 at 7:43:09 PM UTC-5, Joey Huchette wrote: > > Hey Micah, > This is definitely possible, provided your quadratic constraints are > convex or second-order cone representable. See this section > <https://github.com/JuliaOpt/Gurobi.jl#quadratic-programming-examples> of > the readme for how to set up a QP, and this section > <https://github.com/JuliaOpt/Gurobi.jl#mixed-integer-programming> for how > to specify integer variables. Also check out our modeling package JuMP > <https://github.com/JuliaOpt/JuMP.jl> for an algebraic modeling language > that I’d recommend using over the lower-level Gurobi interface directly. > > Also, there’s a julia-opt mailing list > <https://groups.google.com/forum/#!forum/julia-opt> we’ve set up for > these types of questions related to optimization in Julia. > > On Saturday, January 17, 2015 at 6:19:59 PM UTC-5, Micah McClimans wrote: > > I'm trying to figure out how to set up a Mixed Integer Quadratic Program >> in Gurobi through Julia, and I'm not seeing how to do it. I'm not seeing >> anything in the source code that even suggests that it can be done, but >> since I can't see anything in the Gurobi docs explaining how to do it >> either, I could very well be missing something important. I'd like to avoid >> actually modifying the Gurobi package, since I could easily screw something >> up, but if MIQP can't be done in Gurobi/Julia, I suppose I would. >> > >
