The following free textbooks and notes serve as useful alternative or supplementary references for the topics covered in this book.
Optimization and Linear Programming
A First Course in Optimization by Jon Lee
Convex Optimization by Boyd and Vandenberghe
Understanding and Using Linear Programming by Matousek and Gärtner (free via Springer with university account)
Linear Programming Notes by Michel Goemans (MIT)
Decision Modelling by David M. Tulett (open text on decision analysis and optimization modeling)
Discrete Mathematics and Combinatorics
Discrete Mathematics: An Open Introduction by Oscar Levin (CC-BY-SA)
Applied Combinatorics by Keller and Trotter (CC-BY-SA 4.0)
Book of Proof by Richard Hammack (proof techniques)
A First Course in Linear Algebra by Robert Beezer
A Byte of Python (CC-BY-SA, free online textbook)
For optimization software, solver tutorials, and modeling language resources, see Appendix E. Additional example code is available at https://github.com/open-optimization/open-optimization-or-examples.
The linear algebra appendix adapts material from A First Course in Linear Algebra by Ken Kuttler and Ilijas Farah, with adaptations by the Lyryx Learning Team, used under the Creative Commons Attribution license (CC BY 4.0, https://creativecommons.org/licenses/by/4.0/). The original open text is available at https://lyryx.com/first-course-linear-algebra/. As adapted for this book, the material is distributed under the book’s CC BY-SA 4.0 license. See the Sources and Attribution chapter in the front matter for complete source and license details.
Portions of the Python and simplex lab material adapt Foundations of Applied Mathematics (Volume 2: Algorithms, Approximation, and Optimization) by Jeffrey Humpherys and Tyler Jarvis, developed with E. Evans, R. Evans, J. Grout, J. Whitehead, and more than sixty student contributors at Brigham Young University. The material is used under the Creative Commons Attribution license (CC BY 3.0 US, https://creativecommons.org/licenses/by/3.0/us/) and, as adapted here, is distributed under this book’s CC BY-SA 4.0 license.
The source labs and the complete contributor list are available at https://github.com/Foundations-of-Applied-Mathematics. See the Sources and Attribution chapter in the front matter for complete source and license details.