Description:  This course presents the theoretical, computational and practical aspects of
nonlinear programming (NLP).  Roughly the first half of the semester will deal with
unconstrained nonlinear optimization problems while the second half will treat constrained problems.
A balance of theory and algorithms will be presented.  Specific topics include:

• steepest descent
• Newton's method
• quasi-Newton methods
• Broyden family methods, BFGS.
• Conjugate gradient methods
• Levenberg Marquart
• Nonlinear least squares
• Method of Lagrange multipliers
• Quadratic programming
• penalty and barrier functions

Prerequisites: M261 or M315.  M369 or equivalent linear algebra recommended.

Contact Information: Professor Kirby, kirby@math.colostate.edu, Weber 134
Time: Tuesday and Thursday 2:10-3:25
Place: B103 (Note room change)
Textbook: Practical Methods of Optimization, R. Fletcher