Course Number

EMIS 8381

Catalog Description

Topics include convexity analysis, nonlinear duality theory, Kuhn-Tucker conditions, algorithms for quadratic programming, separable programming: gradient and penalty methods.

Goals

To learn both the theoretical and practical aspects of models and algorithms for nonlinear optimization problems. To provide a thorough grounding in the fundamental mathematics that underpin the analysis and explore industrial applications of this important class of decision problems.

Prerequisites

EMIS 8371

Recent Instructor

Richard Helgason