Introduction to Optimization, ECE490/CSE441

The course deals with basic theory and methods for the solution of optimization problems; iterative techniques for unconstrained minimization; linear and nonlinear programming with engineering applications; – see course outline with a tentative timeline.

Prerequisites: basics of real analysis in several variables and linear algebra.

Class meets 11-12:20am, Tuesdays and Thursdays in 2017 ECEB. My office hours are scheduled on request.

The synopses of the lectures, homework assignments etc will be posted here.

Textbook for the course is Foundations of Optimization by Osman Guler.
Further sources: Introductory lectures on convex optimization, by Yu. Nesterov.

Grading: there will be 5 homework assignments (totaling 40%), midterm (25%, tentatively on March 5) and comprehensive final exam (35%). Some of the homework will require a modicum of coding; Python, Matlab, Mathematica are fine as coding languages.

Those registered for 4 credits will be required to do a project (groups of 2-3 students are encouraged) to be presented at the final weeks of the course: the project will be reporting on a paper or solving an optimization problem, with a computational component. The projects will be assigned by March 10.