As I hope you know, deterministic global optimisation only works on box-constrained problems, i.e., problems with finite variable bounds. While we can derive finite bounds from certain mathematical structures even if you don’t define said bounds, it’s not always possible, and tbh the solver will be slow AF if you define very variable ranges because:

• The search space is larger
• Your model is likely to be badly scaled
• It’s a sign that you’re either a wee bit lazy and/or that you don’t have a good understanding of the system you are modelling, and this will most likely be reflected in how well you built the model in the first place.

In order to counter user n00bness, this option sets a default bound for unbounded variables. If you do not provide bounds for a variable, its bounds will be automatically set to ±INFINITY.

Reducing this number can greatly improve performance.