Tobias Achterberg

This is a tough question. How to choose parameters to find good solutions quickly depends heavily on the type of problems you are solving. As far as I understand, a main issue with your models is t...

Sure. You can install a callback, which is then called at every single node in the search tree. And you can call the abort() method to stop the MIP search. But I don't understand how this would hel...

No, unfortunately not. Gurobi's data structures and algorithms are designed for a fixed number of variables during the solving process. Hence, if you add more variables, you need to start from scra...

I am not sure whether I understand your question correctly, but maybe the following explanation is of help. First, Gurobi does not support branch-and-price, so you cannot solve an MIP to optimality...

The issue usually arises from parallel solves. In our parallel MIP solver we first process a bunch of nodes without any user interaction in parallel. Then, at the synchronization point, we present ...

Sure, you can just use an all-zero objective function. Then the problem is a pure feasibility problem, which of course is fine for KKTs.

It should not matter as long as presolve is enabled. From a practical point of view, range constraints in Gurobi are a bit painful because adding a range constraint will actually add an equation an...

For fractions you can of course just multiply the whole constraint by the smallest common multiplier of your denominators. So, instead of writing 1/3x + 2y <= 7 you would write x + 6y <= 21. For ro...

What your code is implicitly doing is to create a "model" object with the default constructor. Then, you are creating another GRBModel object passing the "env" to it and assign this using the assig...

You are adding variables with model.addVar() from within your callback? This just cannot work. What you have in your hand as a user is the original user model. But the branch-and-cut is performend ...