ECE 58000 - Optimization Methods for Systems And ControlLecture Hours: 3 Credits: 3 Professional Attributes
Normally Offered: Each Spring
Introduction to optimization theory and methods, with applications in systems and control. Nonlinear unconstrained optimization, linear programming, nonlinear constrained optimization, various algorithms and search methods for optimization, and their analysis. Examples from various engineering applications are given.
- An Introduction to Optimization, 4th Edition, E. K. P. Chong and S. H. Zak, John Wiley & Sons, Inc., 2013, ISBN No. 9781118279014.
Recommended Text(s): None.
Learning Outcomes:A student who successfully fulfills the course requirements will have demonstrated:
- an ability to formulate optimization problems and identify possible solutions to such problems. 
- an ability to apply and analyze basic linear and nonlinear optimization algorithms. 
- a background needed to understand more advanced optimization techniques. 
- an ability to make formal and rigorous arguments in analyzing optimization problems and solution techniques. 
|1-3||INTRODUCTION - Motivating examples (1) - Mathematical preliminaries (2)|
|4-13||UNCONSTRAINED OPTIMIZATION - First and second order conditions (2) - Algorithms for unconstrained optimization: one dimensional search methods; gradient methods; Newton methods; conjugate direction methods; quasi-Newton methods (8)|
|14-16||LEAST SQUARES ANALYSIS - Examples and basic properties (2) - Recursive least squares algorithm (1)|
|17-19||RANDOM SEARCH ALGORITHMS - Simulated annealing (1) - Genetic algorithms (2)|
|20-28||LINEAR PROGRAMMING - Examples and basic properties (4) - Simplex method (2) - Duality (3)|
|29-38||NONLINEAR CONSTRAINED OPTIMIZATION - Lagrange and second order conditions (5) - Karush-Kuhn-Tucker and second order conditions (4) - Algorithms for constrained optimization (1)|
|39-42||CONVEX OPTIMIZATION - Convexity (2) - Optimality conditions (2)|