Maliheh Aramon

If I copy the model by model.copy, will the copied model utilize the previously computed solution? No, you would need to set the Start attributes on the variables of the copied model in this ca...

Hi Ali,  When I add constraints to enforce those feasible solutions, the entire model becomes infeasible. This suggests that the solutions you expect to be feasible may not be feasible. You can i...

Or should I explicitly set var.Start = var.X, for those variables included in the first run? As long as you do not call the reset() method on the model object, the solver will utilize the previou...

Can I interpret it as the bottleneck in this particular problem is proving the solution is optimal rather than finding the solution?  This depends on the model and the quality of the start soluti...

Hi Ruixuan, Any changes to the model, including setting the Start attributes on the variables, reset the solve process. The Gurobi Optimizer uses the previous solution solely as the start solution....

Hi,  The gurobipy module was restructured a bit for version 12.0. This should do the trick in version 12.0: from gurobipy import GRBd = {getattr(GRB.Status, k): k for k in GRB.Status.__dir__() if "...

I need to build the large model once and, solved it in each iteration only the variables associated to pair (key, value) of my dictionary. What happens to the variables that are not part of the k...

Hi,  I am not sure that I fully understand your question. Given your snippet, it is not clear what you changed on the model in each iteration of the "for" loop. Would you like to build and solve a ...

Hi Benjamin, As outlined in the documentation on multiple objectives, Gurobi provides an API to solve multi-objective optimization problems using three main approaches: 1) blending the objectives, ...

Hi Yanda,  Thank you for contacting us. You can check the "Performance Tuning for Gurobi's Barrier Algorithm" presentation to learn about different strategies to improve barrier performance.  Param...