Welcome to the Pyomo Tutorial, a project currently under development with completion expected by Winter, 2023. These notebooks derives from the Pyomo summer workshop 2018 and we update them with the latest version of Python and Pyomo.
Pyomo is a complete and versatile mathematical optimization package for the Python ecosystem. Pyomo provides a means to build models for optimization using the concepts of decision variables, constraints, and objectives from mathematical optimization, then transform and generate solutions using open source or commercial solvers.
All notebooks in this repository can be opened and run in Google Colab. A launch icon appearing at the top of a page (look for the rocket) indicates the notebook can be opened as an executable document. Selecting Colab will reopen the notebook in Google Colab. Cells inside of the notebooks will perform any necessary installations of Pyomo and solvers needed to execute the code within the notebook.
Start your journey with the first chapter!
We seek your feedback! If you encounter an issue or have suggestions on how to make these examples better, please open an issue using the link at the top of every page (look for the Github cat icon).
We are a group of researchers and educators who came together with a common purpose of developing materials for use in our classroom teaching. Hopefully, these materials will find use in other classrooms and, most importantly, by those seeking entry into the world of mathematical programming.
- David Bernal, Purdue University
- Zedong Peng, Purdue University
- Albert Lee, Purdue University