References

If a single reference book on nonlinear optimization is to be recommended, be it [1] that sits on your book shelf.

If one or two more can still fit, [2], [3] are classical comprehensive references on nonlinear programming (the latter covers linear programming too).

While all the three books are only available for purchase, there is a wealth of resources that are freely available online such as the notes [4] accompanying a course on optimal control, which do a decent job of introduction to a nonlinear programming, and beautifully typeset modern textbooks [5] and [6], the former based on Julia language. Yet another high-quality textbook that is freely available online is [7].

When restricting to convex optimization, the bible of this field [8] is also freely available online. It is a must-have for everyone interested in optimization. Yet another advanced and treatment of convex optimization is [9], which is also freely available online.

Maybe a bit unexpected resources on theory are materials accompanying some optimization software. Partilarly recommendable is [10], it is very useful even if you do not indend to use their software. In particular, their introduction to conic optimization is very well written and easy to follow.

References

[1]

J. Nocedal and S. Wright, Numerical Optimization, 2nd ed. in Springer Series in Operations Research and Financial Engineering. New York: Springer, 2006. Available: https://doi.org/10.1007/978-0-387-40065-5

[2]

D. Bertsekas, Nonlinear Programming, 3rd ed. Belmont, Mass: Athena Scientific, 2016. Available: http://www.athenasc.com/nonlinbook.html

[3]

D. G. Luenberger and Y. Ye, Linear and Nonlinear Programming, 5th ed. in International Series in Operations Research & Management Science, no. 228. Cham, Switzerland: Springer, 2021. Available: https://doi.org/10.1007/978-3-030-85450-8

[4]

S. Gros and M. Diehl, “Numerical Optimal Control (Draft).” Systems Control; Optimization Laboratory IMTEK, Faculty of Engineering, University of Freiburg, Apr. 2022. Available: https://www.syscop.de/files/2020ss/NOC/book-NOCSE.pdf

[5]

M. J. Kochenderfer and T. A. Wheeler, Algorithms for Optimization. The MIT Press, 2019. Accessed: Dec. 29, 2020. [Online]. Available: https://algorithmsbook.com/optimization/

[6]

J. R. R. A. Martins and A. Ning, Engineering Design Optimization. Cambridge ; New York, NY: Cambridge University Press, 2022. Available: https://mdobook.github.io/

[7]

M. Bierlaire, Optimization: Principles and Algorithms, 2nd ed. Lausanne: EPFL Press, 2018. Available: https://transp-or.epfl.ch/books/optimization/html/OptimizationPrinciplesAlgorithms2018.pdf

[8]

S. Boyd and L. Vandenberghe, Convex Optimization, Seventh printing with corrections 2009. Cambridge, UK: Cambridge University Press, 2004. Available: https://web.stanford.edu/~boyd/cvxbook/

[9]

A. Ben-Tal and A. Nemirovski, “Lectures on Modern Convex Optimization - 2020/2021/2022/2023 Analysis, Algorithms, Engineering Applications,” Technion & Georgia Institute of Technology, 2023. Available: https://www2.isye.gatech.edu/~nemirovs/LMCOLN2023Spring.pdf

[10]

“MOSEK Modeling Cookbook.” Mosek ApS, Sep. 2024. Available: https://docs.mosek.com/MOSEKModelingCookbook-a4paper.pdf