Preface

These are class notes for a quarter long course on Introduction to Optimization (Math 368) at Northwestern University taught during the Winter and Spring of 2022. The class is aimed at upper-level undergrads who’ve completed a basic sequence in linear algebra and calculus. The prerequisites for the linear programming part are Gaussian elimination and basic theorem proving. For the non-linear programming part, you’ll need to know basic properties of gradients and directional derivatives.

The textbook used in the class was Linear Programming, Foundations and Extensions, by Robert J. Vanderbei. The textbook is freely available to Northwestern students via SpringerLink. The textbook was used mainly as a reference for examples and exercises.

These notes are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. Any suggestions and improvements to the notes are welcome and greatly appreciated. You can send me an email or open an issue on Github.