# Recommendations for solver and options to solve a MIQP, just looking for a feasible solution **URL:** \ **Category:** Optimization (Mathematical)\ **Tags:** gurobi, quadratic, integer\ **Created:** [December 1, 2023, 11:28pm UTC](https://discourse.julialang.org/t/recommendations-for-solver-and-options-to-solve-a-miqp-just-looking-for-a-feasible-solution/107024 "2023-12-01T23:28:22Z")\ **Posts on this page:** 1\ **Showing post:** 2

**Author:** ![odow](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/odow/32/28685_2.png) [@odow](https://discourse.julialang.org/u/odow)\ **Post date:** [December 2, 2023, 2:12am UTC](https://discourse.julialang.org/t/recommendations-for-solver-and-options-to-solve-a-miqp-just-looking-for-a-feasible-solution/107024/2 "2023-12-02T02:12:30Z")

First, MIQP problems are difficult to solve. Especially ones with 354,000 binary variables! The answer you’re looking for is highly problem dependent, so if you can post a reproducible example, people may have suggestions for modeling improvements. Trying to tune the solver is probably of little benefit. > Are there any **other solvers** that I should try and see if they’re faster? I’m not paying for a solver, though. You don’t have many options, unfortunately. If you’re an academic, I’d suggest Gurobi. Otherwise it’s mainly SCIP. Other options like Bonmin are likely to also struggle. > As far as I understand all quadratic programs are convex This is not true. `x^2 <= 1` is convex, `x^2 >= 1` is non-convex. (The feasible region is `x <= -1` and `x >= 1`. The range `x in (-1, 1)` is infeasible.) Similarly, `min x^2` is convex, `max x^2` is non-convex. Also, terms like `x * y` are non-convex. --- _[View the full topic](https://discourse.julialang.org/t/recommendations-for-solver-and-options-to-solve-a-miqp-just-looking-for-a-feasible-solution/107024)._