Lennart Lahrs

Hello Sebastián, The Method and Crossover parameters only affect the algorithm for the initial root relaxation of your MIP. What follows when solving a MIP is the Branch and Bound algorithm. The al...

Hi Shaojie,You can express this type of objective using auxiliary variables. Please find below some comments and a code example that I hope will help you with your problem. Gurobi can handle bilin...

Hi Gabriel, Sequentially solving your model for different objectives rather than solving your model for one combined objective can have a strong influence on model performance and solving behavior....

Hi Frederico, Please find below a suggestion of how to access objective values and the Xn attribute of Gurobi model variables for multiple solutions in Pyomo. import pyomo.environ as pem = pe.Concr...

Hi Joyjit, You were missing a for-loop in one of your constraint formulations, which caused unintended behavior. Please find the updated constraint formulation below. I highly recommend using gp.qu...

Hi Fatih,Although Gurobi does not directly support constraints containing more general multilinear terms, they can be modeled using a series of bilinear constraints. In your case, you must extend y...

Hi Mayukh,Can you please provide a complete piece of code to reproduce your error? We have a tutorial on preparing a minimal reproducible example for cases like these.Best regards,Lennart

Hi Joyjit,Based on your description I would expect the primary objective to only contain \(\texttt{z_upbound}\), without the sum of all entries of \(\texttt{t_expupdated}\).Otherwise, I am not able...

Hi Hancheng, The Gurobi API is intentionally designed to be used from a single thread per environment. That is by design to make model construction and data access as fast as possible without stori...

As of 2023, this article might be more relevant during your license request in portal.gurobi.com.Best,Lennart