Lars Ruthotto

MATH 571 - Numerical Optimization

Prof. Lars Ruthotto
Additional course material will be made available using Canvas.
MoWe 11:30 - 12:15 PM, Math & Science Center, Room E408
First day of classes: August 28, 2018
Last day of classes: December 5, 2018
Recess: September 7 (Labor Day), October 12 (Fall Break)
This course provides students with an overview of state-of-the-art numerical methods for solving both unconstrained and constrained, large-scale optimization problems. Algorithm analysis and development will be emphasized, including efficient and robust implementations.
In addition, students will be exposed to state-of-the-art software that can be used to solve optimization problems.
The main references are
Numerical Optimization by J. Nocedal and S.J. Wright
Introduction to Nonlinear Optimization by A. Beck
Convex Optimization by S. Boyd and L. Vandenberghe
Homework will be a combination of computing and analysis. Computing will be done using Julia or Matlab.
Solutions, results, and analysis should be submitted as a single, document typeset with LaTeX.
All codes used to generate results for the assignments have to be submitted electronically as a single .zip, .tar, or .tgz archive.
The syllabus can be found here.