We run large-scale optimization problems regularly. They have thousand of variables and tens of thousands of constraints.
Those optimization problems often get numerically instable. In those cases, we fail to pin-point what exactly causes numerical instability (that is a huge pain-point).
We had 2 questions:
- Is it possible to identify what is causing numerical instability in our optimization problem? [Note: Both theoretical techniques and programmatic tool (preferably python-based) would be helpful]
- Given a optimization problem, Is it possible to predict deterministically that would it be Numerically instable or not?