The Ohio State University
Dept. Electrical and Computer Engineering

ECE 5759: Optimization for Static and Dynamic Systems

Instructor: Prof. Kevin M. Passino 416 Dreese Laboratory, passino [at]

Office Hours: Talk to me after class or email me and set up an appointment

Textbook: Dimitri P. Bertsekas, Nonlinear Programming, Second Edition, Athena Scientific Press, 1999.

Course Objectives: The course will involve understanding the basic methods and theory of optimization and gaining experience in solving practical engineering optimization problems.

Topical Outline:

  1. Gradient methods
  2. Gauss-Newton/Levenberg Marquardt methods, quasi-Newton methods conjugate direction methods
  3. Nongradient optimization (pattern/direct search, stochastic methods)
  4. Constrained optimization, and Lagrange methods
  5. Lagrange multiplier algorithms
  6. Duality and convex programming
  7. Fundamental theory (e.g., convergence properties/conditions)
  8. Strategies for optimization problem formulations (modeling)
  9. Examples: Solutions to optimization problems arising in science and engineering
  10. Extensive use of Matlab optimization toolbox

Grading (tentative):

Policy: Work entirely on your own for all assignments. Turn in your own code for programming assignments.


Scheduling: This course is offered in Autumn Quarter


  1. Optimization Technology Center (ANL and Northwestern Univ.)
  2. Mathworks (for links) and their toolbox
  3. Optimization On-Line (eprints, etc.)
  4. J. Nocedal and S. Wright, Numerical Optimization, Springer, NY, 1999.