Migrating to Gurobi makes sense.
Switching solvers may seem like a daunting task, but it’s typically straightforward with Gurobi. 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 on using the Gurobi Optimizer
- Provide support for both MPS and LP file formats
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.
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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:
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?
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Setting Solver Parameters
What solver parameters do I change? What effects are these changes intended to produce?
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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?
