Instructor: 

Prof. Lars Ruthotto

Description: 

Nonlinear optimization problems arise in a wide range of applications, for example, in economics, physics, engineering, machine learning, and imaging. This introductory course covers a variety of relevant unconstrained and constrained optimization problems. While its emphasis is on theory, we will also discuss realworld applications and solve smallscale, smooth optimization problems numerically.

Prerequisites: 

Math 211, Math 221 or 321, Math 250, and CS 170

Times: 

Lectures: MW 2:30 PM  3:45 PM, Math & Science Center, Room E406
First day of classes: August 28, 2018
Last day of classes: December 5, 2018
Tests: September 26 and November 12
Final exam: December 18, 8:00  10:30 AM
Recess: September 3 (labor day), October 8 (fall break)

Literature: 

The primary textbook for the course is the following:
Introduction to Nonlinear Optimization by A. Beck
Reading the textbook is not required, but it is recommended. I will provide references for each lecture. You are not responsible for textbook material that is not covered in lecture.

Syllabus: 

The syllabus can be found here.

Material: 

Additional course material will be made available using Canvas.


Unconstrained optimization: 

Convex optimization: 

Constrained optimization: 

