Algorithms for Optimization

Ancillaries for the textbook

This repository contains resources related to Algorithms for Optimization by Mykel J. Kochenderfer and Tim A. Wheeler (MIT Press, 2019).

Problem definitions

The problem environments used in the book (summarized in Appendix F) have been implemented in the Julia package DecisionMakingProblems.jl.

Code

The code for generating all figures can be found in this repository.

Slides

Slides can be downloaded here.

Syllabi

As more universities begin offering courses based on the textbook (or has as recommended reading), we will link to their public syllabi.

1. Stanford University, AA222: Engineering Design Optimization
2. Purdue University, CS520: Computational Methods in Optimization
3. Carnegie Mellon University, 10-425/10-625: Introduction to Convex Optimization
4. Johns Hopkins University, 685.621.81 - Algorithms for Data Science

Feel free to file a pull request or issue to add additional courses that use the textbook.

Errata

Errata to the print version can be found here. You may also file issue reports there.