MATH 560 Optimization (4 credits)

Note: This is the 20132014 edition of the eCalendar. Update the year in your browser's URL bar for the most recent version of this page, or click here to jump to the newest eCalendar.

Offered by: Mathematics and Statistics (Faculty of Science)

Overview

Mathematics & Statistics (Sci) : Line search methods including steepest descent, Newton's (and Quasi-Newton) methods. Trust region methods, conjugate gradient method, solving nonlinear equations, theory of constrained optimization including a rigorous derivation of Karush-Kuhn-Tucker conditions, convex optimization including duality and sensitivity. Interior point methods for linear programming, and conic programming.

Terms: This course is not scheduled for the 2013-2014 academic year.

Instructors: There are no professors associated with this course for the 2013-2014 academic year.

  • Prerequisite: Undergraduate background in analysis and linear algebra, with instructor's approval