EE 227B: Optimization Theory

Spring 2004

University of California at Berkeley
Dept of Electrical Engineering & Computer Sciences



Instructor:        

       Elijah Polak, 255M Cory, polak@eecs.berkeley.edu    

Class time:

TU:
4:00-6:00pm
425 LATIMER HALL
WE:
4:00-5:00pm
293 CORY HALL


Text:        Optimization: Algorithms and Consistent Approximations, E. Polak, Springer, 1997. 


Announcements:

·       Make sure you registered for the class for grade or pass/fail. This class will NOT allow any auditors.

Lecture Notes:                                               

Lecture Notes

Assigned Reading*

  Outline

Lecture 01: Optimization in Engineering

OACA 5.1

Lecture 02: Mathematical Preliminaries

OACA 5.2, 5.4op, 5.5op

Lecture 03: Gradient Methods

OACA 5.3, 1.3

Lecture 04: Rate of Convergence & Efficiency

OACA 1.2

Lecture 05: Newton’s Method

 OACA 1.4

Lecture 06: Conjugate Gradient Methods

 

Lecture 07: Line Search Methods

 

Lecture 08: Quasi-Newton Methods

 

Lecture 09: Minimization of Max Functions

 

Lecture 10: Inequality Constraints

 

Lecture 11: Equality and Inequality Constraints

 

Lecture 12: Penalties, Sensitivity and Duality

 

Lecture 13: Unconstrained Optimal Control

 

Lecture 14: SQP Methods

 


*Legend: (OACA) – Main Text; op – Operational Knowledge (of theorems, etc)


Grading: Prepare and present a one hour lecture on a selected topic.  


Supplemental Texts:

Convex Analysis and Optimization, by D. Bertsekas, A. Nedic and A. Ozdaglar, Athena Scientific; 2003

Nonlinear Programming, by D. Bertsekas, Athena Scientific; 2nd Edition, 1999

Treatise on Analysis, by J. A. Dieudonne, Academic Press; 1978

Convex Analysis, by R. T. Rockafellar, Princeton University Press; 1970

Real and Complex Analysis, by W. Rudin, Mc-Graw Hill; 3rd Edition, 1986