6.252J | Spring 2003 | Graduate

Nonlinear Programming

Course Description

6.252J is a course in the department's "Communication, Control, and Signal Processing" concentration. This course provides a unified analytical and computational approach to nonlinear optimization problems. The topics covered in this course include: unconstrained optimization methods, constrained optimization methods, …
6.252J is a course in the department’s “Communication, Control, and Signal Processing” concentration. This course provides a unified analytical and computational approach to nonlinear optimization problems. The topics covered in this course include: unconstrained optimization methods, constrained optimization methods, convex analysis, Lagrangian relaxation, nondifferentiable optimization, and applications in integer programming. There is also a comprehensive treatment of optimality conditions, Lagrange multiplier theory, and duality theory. Throughout the course, applications are drawn from control, communications, power systems, and resource allocation problems.
Learning Resource Types
Lecture Notes
Textbook cover of D. P. Bertsekas, Nonlinear Programming: 2nd Edition.
Photo of the course textbook cover, written by the course instruction, Prof. Dimitri Bertsekas. (Image courtesy of Dimitri Bertsekas and Athena Scientific.)