Modeling Examples in Jupyter Notebook

These Jupyter Notebook modeling examples illustrate important features of the Gurobi Python API modeling objects, such as adding decision variables, building linear expressions, adding constraints, and adding an objective function for a mathematical optimization model. In addition, they explain more advanced features such as generalized constraints, piece-wise linear functions, multi-objective hierarchical optimization, as well as typical types of constraints such as allocation constraints, balance constraints, sequencing constraints, precedence constraints, etc. These modeling examples also show how the modeling objects of Gurobi and the typical type of constraints can be used in different contexts.

 

These modeling examples:

  • Illustrate the broad applicability of mathematical optimization.
  • Show how to build mathematical optimization models.
  • Are coded using the Gurobi Python API in Jupyter Notebook.

 

Modeling Examples:

 

Modeling Tutorial:

 

Commercial License

New Users: Gurobi allows you to try a free, full-featured, commercial evaluation license for 30 days. During that time, you’ll also get:

  • Free benchmarking services
  • Free model tuning services
  • Access to Gurobi’s world-class technical support
  • Two free hours of one-on-one consulting services

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

 

Note to Academic Users: Academic users at recognized degree-granting institutions can get a free academic license. You can learn about our academic program here. Can’t view the form? Please click here to open it in a new window.

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