Switching solvers may seem like a daunting task, but it’s typically straightforward with Gurobi—and new customers regularly tell us they’re happy they made the switch. We make it easy to get started with:

• A wide range of simple and intuitive interfaces, so you can work in the environment you are most comfortable with

• User-friendly Quick Start and Reference Guides to reduce your learning curve

• Support for both MPS and LP file formats

• An expert support team that will guide you every step of the way as you switch to Gurobi

You may also be interested in boosting your mathematical optimization modeling skills with Python. Our example library gets you up and running fast with our Python API.  Explore our on-demand webinars and Gurobi Jupyter Notebook examples to learn more.

Three Steps to Migration​

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

• Model-building Considerations – Different APIs allow you to build models in different ways. For example, in addition to the traditional term-based formulation, our Python API allows you to use pandas or SciPy matrices, which may be much more efficient for your use case.

• Setting Solver Parameters – Consider the solver parameters you need to change, and the effects these changes will have on your model.

• Computing and Extracting the Solution – Think about the type of solution you want and the parameters necessary to obtain it. For example, you may need multiple solutions that satisfy a minimum quality level. Or, perhaps you just want a good-enough, feasible solution. With that goal in mind, consider the most efficient method for extracting your solution.

Have questions or need assistance with any of the above steps? Our free evaluation license includes access to our expert support team, who are here to help you succeed.