Syllabus

Course Meeting Times

Lectures: 2 sessions / week, 1.5 hours / session

Recitations: alternating weeks, 1 hour / session

Professor Dimitri P. Bertsekas

Course Description

A unified analytical and computational approach to nonlinear optimization problems. Unconstrained optimization methods include gradient, conjugate direction, Newton, and quasi-Newton methods. Constrained optimization methods include feasible directions, projection, interior point, and Lagrange multiplier methods. Convex analysis, Lagrangian relaxation, nondifferentiable optimization, and applications in integer programming. Comprehensive treatment of optimality conditions, Lagrange multiplier theory, and duality theory. Applications drawn from control, communications, power systems, and resource allocation problems.

Textbook

Bertsekas, Dimitri. Nonlinear Programming: 2nd Edition. Belmont, MA: Athena Scientific Press , 1999. ISBN: 1886529000.

Grading

In-class midterm (30%)
3-hour final (40%)
Problem Sets (30%)

Course Info

Learning Resource Types

notes Lecture Notes