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. >
