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] ece.osu.edu
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.
- Gradient methods
- Gauss-Newton/Levenberg Marquardt methods, quasi-Newton methods conjugate direction methods
- Nongradient optimization (pattern/direct search, stochastic methods)
- Constrained optimization, and Lagrange methods
- Lagrange multiplier algorithms
- Duality and convex programming
- Fundamental theory (e.g., convergence properties/conditions)
- Strategies for optimization problem formulations (modeling)
- Examples: Solutions to optimization problems arising in science and engineering
- Extensive use of Matlab optimization toolbox
- Homeworks, 25%
- Projects, 45%
- Final examination, 30%
Policy: Work entirely on your own for all assignments. Turn in your own code for programming assignments.
- Linear algebra
- Comfort with a level of mathematical sophistication
- Matlab programming experience