NONLINEAR OPTIMIZATION

Graduate

This course is a study of unconstrained optimization, optimality conditions (necessary, sufficient and Karush-Kuhn-Tucker), penalty functions, convex functions, and convex programming. Upon completion, students should be able to formulate a variety of advanced continuous optimization problems; determine the appropriate solution technique or algorithm for a given problem; implement relevant algorithms and analyze their effectiveness. In addition, students should demonstrate a deep understanding of the mathematical theory behind algorithms and other solution techniques. This course is cross-level listed with AMS 4680. Credit cannot be received for both MCS 8680 and AMS 4680. PREREQUISITE: Admission to a graduate program in Science HOURS OF CREDIT: 3