Introduction to Gurobi Jupyter Notebook Modeling Examples
Gurobi Jupyter Notebook Modeling Examples are mathematical optimization models coded using the Gurobi Python API and implemented with Jupyter Notebooks (which are web applications that let you create and share documents that contain live code, equations, visualizations, and narrative text).
With Gurobi Jupyter Notebook Modeling Examples, you will learn how to translate a business, engineering, or scientific problem into a mathematical optimization model.
These modeling examples:
- Instruct users on how to build mathematical optimization models.
- Illustrate the broad applicability of mathematical optimization across various industries.
- Explain the 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.
The examples are taken from real-world use cases, and teach you how to solve problems, such as the traveling salesman problem, marketing campaign optimization, electrical power generation, and more.
No matter if you are a beginner, intermediate or an advanced user, these Jupyter Notebook Modeling Examples will help you improve your optimization modeling skills using Python.
Explore Our List of Examples to Find the Level That Is Right For You