Lars Ruthotto

MATH 347 - Introduction to Nonlinear Optimization

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 real-world applications and solve small-scale, 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:
Math347-Himmelblau
    Convex optimization:
Math347-Himmelblau
    Constrained optimization:
Math347-Himmelblau