IE 521 - Nonlinear Programming
Industrial Engineering, Penn State University
The study of the fundamental theory of optimization. Topics include classical optimization, convex analysis, optimality conditions and duality, algorithmic solution strategies.
Text: Nonlinear Programming: Theory and Algorithms, 3rd edition, by M.S. Bazarra, H.D. Sherali, & C.M. Shetty, Wiley, 2006
Prerequisites: IE 505 - Linear Programming
- Course Topics:
- Convex Analysis
- Convex Sets
- Convex Functions
- Generalized Convexity
- Optimization Results Involving Convex Functions &
Convex Sets
- Theorem of the Alternative
- Fritz-John Optimality Conditions
- Langrangian Duality
- Algorithmic Maps and Applications
- Zangwill's Convergence Theorem
- Line Search Techniques
- Multidimensional Search Techniques
- Methods of Conjugate Directions
- Penalty and Barrier Function Methods
- Reduced Gradient Algorithm
- Subgradient Optimization
- Quadratic Programming
Last modified: September 23, 2001
|
