Computational methods in optimization

David Gleich

Purdue University

Spring 2012

Course number CS 59000-OPT

Tuesday and Thursday, 3:00-4:15pm

Lawson B134

References

Background classes

• Gilbert Strang, Introduction to Linear Algebra. MIT OpenCourseWare http://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010/

Other courses

• Walter Murray, Numerical optimization, Stanford http://www.stanford.edu/class/cme304/
• Michael Saunders, Large-scale numerical optimization, Stanford http://www.stanford.edu/class/msande318/
• Diane O’Leary, Advanced numerical optimization, Univ. of Maryland http://www.cs.umd.edu/~oleary/a607/
• Michael P. Friedlander, Numerical optimization, UBC http://www.cs.ubc.ca/~mpf/cs546-11/

Online sites

• Wikimization run by Jon Dattorro

Textbooks

Optimization is a rich field. Here are other “freely” available resources at Purdue.

• Primal-dual interior-point methods by Stephen J. Wright, SIAM 1997.
• Numerical methods for least squares problems by Åke Björck, SIAM 1996.
• Convex optimization by Stephen Boyd and Lieven Vandenberghe, Cambridge University Press, 2004.
• A mathematical view of interior-point methods in convex optimization by James Renegar, SIAM 2001.
• Linear programming with MATLAB by Michael C. Ferris, Olvi L. Mangasarian, and Stephen J. Wright, SIAM 2007.
• Trust region methods by Andrew R. Conn, Nicholas I. M. Gould, and Philippe L. Toint, SIAM 2000.

Software

Free

(Matlab) CVX by Michael Grant and Stephen Boyd

(C/MPI) TAO by Argonne National Labs

(C/MPI) Trilinos by Sandia National Laboratories; see NOX (Nonlinear)

(Matlab) Poblano by Danny Dunlavy, Tammy Kolda and Evrim Acar :

Commerical

Gurobi, free academic license and GurobiMex

Other lists

http://www.mat.univie.ac.at/~neum/glopt/software_l.html

http://en.wikipedia.org/wiki/List_of_optimization_software