This repository contains optional Jupyter notebooks for the EPFL course MATH-265, Introduction to optimization and operations research.
The notebooks complement the lectures and paper-based exercise sessions. They can help you visualize mathematical objects, follow algorithms step by step, and experiment with the concepts studied in the course.
Programming is not assessed in the exam. You are not expected to complete all the notebooks.
Most exercises are provided in pairs:
*_questions.ipynbcontains the questions and incomplete code;*_responses.ipynbcontains the complete code and explanations.
You may attempt the question notebook first, consult the complete response if you get blocked, or simply read and execute the response notebook as an interactive illustration. The response notebooks are available immediately because this material is intended for independent study.
The weekly exercise sheets identify a small selection of recommended notebooks. The remaining notebooks are available for students who would like to explore a topic further.
00-python— optional Python introduction01-introduction— modeling and basic concepts02-linear_optimization— linear constraints03-simplex— simplex method04-duality— duality05-networks— networks and flows06-transhipment— transhipment models07-shortest-paths— shortest-path algorithms08-discrete— discrete optimization09-nonlinear— nonlinear optimization
To run the notebooks locally, install the dependencies with:
python -m pip install -r requirements-notebooks.txt