— Numerical Optimization

Prerequisites & course information

This version has ended; see updated course, below. Course Description: Numerical methods for infinite dimensional optimization problems. Newton and Quasi-Newton methods, linear and sequential quadratic programming, barrier methods; large-scale optimization; theory of approximations; infinite and semi-infinite programming; applications to optimal control, stochastic optimization and distributed systems. Learning Activities: Lecture 3 hour(s), Term Paper/Discussion 1 hour(s). Grade Mode: Letter. MAT 258A — Numerical Optimization (4 units) Course Description: Numerical methods for infinite dimensional optimization problems. Newton and Quasi-Newton methods, linear and sequential quadratic programming, barrier methods; large-scale optimization; theory of approximations; infinite and semi-infinite programming; applications to optimal control, stochastic optimization and distributed systems. Prerequisite(s): MAT 025; MAT 167 . Learning Activities: Lecture 3 hour(s), Term Paper/Discussion 1 hour(s). Enrollment Restriction(s): Open to graduate students; open to undergraduate students with consent of instructor. Grade Mode: Letter. This course version is effective from, and including: Winter Quarter 2027. Learning Activities: Lecture 3 hour(s), Term Paper/Discussion 1 hour(s). Grade Mode: Letter. MAT 258A — Numerical Optimization (4 units) Course Description: Numerical methods for infinite dimensional optimization problems. Newton and Quasi-Newton methods, linear and sequential quadratic programming, barrier methods; large-scale optimization; theory of approximations; infinite and semi-infinite programming; applications to optimal control, stochastic optimization and distributed systems. Prerequisite(s): MAT 025; MAT 167 . Learning Activities: Lecture 3 hour(s), Term Paper/Discussion 1 hour(s). Enrollment Restriction(s): Open to graduate students; open to undergraduate students with consent of instructor. Grade Mode: Letter. This course version is effective from, and including: Winter Quarter 2027.