MATH 651 - Optimization Algorithms

Credits: [3]

Description: Design and analysis of algorithms for linear and non-linear optimization; first-order numerical methods for unconstrained optimization (line-search methods, steepest-descent method, trust-region method, conjugate-gradient method, quasi-Newton methods, methods for large scale problems); Newton’s method; numerical methods for linear programming (simplex methods, interior-point methods); numerical methods for constrained optimization (penalty, barrier, and augmented-Lagrangian methods, sequential quadratic programming method).
Course ID: 055305
Prerequisite: Prerequisite: MATH 221, MATH 251, or consent of instructor. MATH 650 recommended.
Components: Lecture
Grading Method: A-F, Audit