Argonne National Laboratory Mihai Anitescu, Ph.D, Computational Mathematician
Mathematics and Computer Science (MCS) Division
Comp Math 310, Part B: Optimization

Stat 310: Computational Math and Optimization II: Simulation and Optimization


  • First Lecture: Feb 9, 2010. Last lecture: Mar 11, 2010.

  • Office Hours: Tue-Thu 3-5 pm, Eckhart 120A, or by appointment.

Course Outline


  1. Homework 1, due 02/18/2010.
  2. Homework 2, due 02/25/2010.
  3. Homework 3, due 03/04/2010.
    • To install intval: Download it in a directory over which you have read write access. Unpack the archive (for example, by using gzip -d filename.tar.gz followed by tar -xvf filename.tar). Add the directory and all subdirectories to your matlab path. Simplest thing is to do, from the matlab interface: File->Set Path->add with subfolders then browse until you find the directory where intval was unpacked. I would restart Matlab, though that is not necessary. First time around, intval runs an installation/demo routine which takes a while to run, but second time around matlab start should be fast, while allowing you to see the intval demo movie.
  4. Homework 4, due 03/11/2010.
  5. Homework 5, due 03/17/2010


  1. Textbook: Nocedal and Wright, "Numerical Optimization", Springer, 2006. Available online for free for members of the University of Chicago Community.
  2. Dimitris Bertsimas' Optimization Course at MIT .
  3. Dimitri Bertsekas' Convex Analysis and Optimization Course at MIT
  4. Dimitri Bertsekas' Nonlinear Programming Course at MIT
  5. Harvey Greenberg's Myths and Counterexamples in Mathematical Programming page on the INFORMS site.
  6. The Matlab Exchange: A large set of free Matlab Programs contributed by Matlab Users. I start here many times when designing and developing a new project
  7. The Matlab Documentation page, (downloadable pdf).
  8. Tim Kelley's collection of Matlab Programs for Optimization..
  9. LSTRS, a Matlab large-scale trust-region algorithm implementation.
  10. The AMPL modeling language web site.

What I assume is known by the students.

  1. Multivariate calculus.
  2. First-order necessary optimality conditions for unconstrained optimization.
  3. Linear algebra. Positive definite and semidefinite symmetric matrices, eigenvalues.
  4. Beginner Matlab.

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Last modified: February 11, 2010