Making The Switch To Gurobi
Is Easier Than You Think

Learn why companies are switching to Gurobi for better performance, support and licensing.




Migrating to Gurobi makes sense.

We know making the decision to switch can be difficult, so before you make that decision, get 2 FREE hours of one-on-one consulting with our world-class, award winning team! Be confident that your next move is the RIGHT move

Switching solvers may seem like a daunting task, but it’s typically straightforward. New customers regularly tell us migrating was easier than they expected, and that they are happy they made the switch to Gurobi. On the Gurobi Product Overview page, we mention four things we do to make it easy to get started with Gurobi:

  • Provide a wide range of interfaces, so you can work in the environment you are most comfortable with
  • Keep the interfaces simple and intuitive to reduce your learning curve
  • Include Quick Start and Reference Guides, and Video Overviews on using the Gurobi Optimizer
  • Provide support for both MPS and LP file formats

You may also be interested in learning about our Gurobi Python modeling and development environment. The Gurobi Python Environment combines the benefits a modeling language with the strengths of a programming language. By embedding our set of high-level optimization modeling constructs in the very popular Python programming language, we’ve eliminated the need to choose between working in just a modeling language or just a programming language.



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What you get with your FREE 30 Day Commercial Evaluation License

Note to Existing Customers Affected by COVID-19: Please use the form above to request a temporary license, if you are experiencing difficulties accessing the Gurobi Optimizer.

1. FREE Benching Services

2. FREE Model Tuning Services

3. Access to Gurobi's World-Class Technical Support

4. TWO FREE Hours of One-on-One Consulting Services

Tracy Pesanelli explains why companies are making the switch to Gurobi.

Three Steps to Migration

No matter what programming language you use, you’ll need to consider three points when starting a migration effort:

1. Building the model

How do I build my optimization model? Do I build it one constraint at a time, or do I build an entire constraint matrix?

2. Setting solver parameters

What solver parameters do I change? What effects are these changes intended to produce?

3. Computing and extracting the solution

Am I looking for an optimal solution, or just a good feasible solution? How do I extract the solution produced by the solver?