Math 164: Optimization



An Introduction to Optimization, 4th Edition, by Chong and Zak


  1. Introduction to optimization (video) (slides)

  2. Optimization application: resource constrained revenue maximization (video) (slides)

  3. Optimization applications (video) (slides)

  4. Optimization application: support vector machine (slides) (Matlab demo by Richard Stapenhurst)

  5. Basics of optimization: terminology, types of minimizers, optimality conditions (incomplete video) (slides)

  6. One-dimensional search methods (video) (slides)

  7. Gradient methods (slides)

  8. Newton's method, Modified Newton's method, and the Gauss-Newton method (slides)

    1. Newton's method (video)

    2. The Gauss-Newton method (video)

  9. The Barzilai-Borwein method (slides)

  10. Conjugate direction methods

    1. Linear conjugate direction methods (slides)

    2. Krylov subspace, nonlinear CG, preconditioning (extra slides)

  11. Linear programming

    1. Modeling and basic geometry (slides) (Matlab demo)

    2. The Simplex method (slides)

  12. Basics of nonlinear optimization

    1. Equality-constrained nonlinear optimization, Lagrange multipliers (video) (slides)

    2. Nonlinear optimization with in/equality constraints, KKT conditions (video) (slides)

  13. Algorithms for constrained optimization (slides)

  14. Major subfields of optimization (slides)


  1. Assignment 1. Deadline: Monday, April 6th, 1pm.

  2. all future homework assignments will be posted in Piazza online forum

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