Covers computational methods for constrained optimization. Topics include basic theory, methods for quadratic programming, active set strategies for linear constraints, and penalty and successive quadratic programming methods for nonlinearly constrained problems. Prerequisites: Requires prerequisite course of CSCI 5606 (minimum grade D-). Restricted to graduate students only.
