Do degeneracies and numerical instabilities more likely during the execution of solvers in case of formulations with greater number of constraints and decision variables?

Specific Domains Optimization (Mathematical)
1

I am dealing with a multi-stage mixed-integer stochastic global supply chain optimization problem and want to solve it using the SDDiP algorithm in the SDDP.jl package in Julia.

In this regard, I am conducting preliminary experiments and wondering that are degeneracies and numerical instabilities more likely during the execution of solvers while solving formulations with a greater number of constraints and decision variables.

If yes, is Gurobi likely to be better at solving these large-scale problems than CPLEX, since Gurobi is considered to have greater numerical stability? References to the peer-reviewed material in the answers will be appreciated.

2

This question doesn’t really have an answer. It really depends on the model.

You should read

If you have more questions, it would be helpful if you could provide a reproducible example of your model.

3

Got it. I will read them. Thanks.