Nonlinear Optimization, Spring 2025

This course serves as a modern introduction to the field of optimization. It covers important topics such as convexity, optimality conditions, duality, gradient methods, and Newton’s method. The objective is to provide the foundations of theory and algorithms of nonlinear optimization, as well as to present a variety of applications from diverse areas.

Course Information

• Syllabus

• Instructor: Jiaming Liang

• Teaching Assistant: Youwei Wang

• Meeting Information: 2:00-3:15 pm, Tuesday/Thursday, Harkness Hall 210

• Office Hours

  • 4:00-5:00 pm, Wednesday, Wegmans Hall 2403 (Jiaming Liang)

  • 4:00-5:00 pm, Friday, Wegmans Hall 1219 (Youwei Wang)

• Textbooks

  • Amir Beck. Introduction to Nonlinear Optimization, Second Edition. SIAM, 2023.

• Recommended Readings

  • Dimitri P. Bertsekas. Nonlinear Programming, Third Edition. Athena Scientific, 2016.

  • Stephen Boyd and Lieven Vandenberghe. Convex Optimization. Cambridge University Press, 2004.

  • David G. Luenberger and Yinyu Ye. Linear and Nonlinear Programming, Third Edition. Springer, 2008.

  • Fatma Kilinc-Karzan and Arkadi Nemirovski. Mathematical Essentials for Convex Optimization. Cambridge University Press, 2024+.