Applied MathematicsAM 230 Numerical Optimization

Introduces numerical optimization tools widely used in engineering, science, and economics. Topics include: line-search and trust-region methods for unconstrained optimization, fundamental theory of constrained optimization, simplex and interior-point methods for linear programming, and computational algorithms for nonlinear programming. (Formerly AMS 230.)

Requirements

Basic knowledge of linear algebra is assumed. Enrollment is restricted to graduate students. Undergraduates may enroll by permission of the instructor.

Credits

5

Quarter offered

Winter

Instructor

Qi Gong