MATH 519/619 Optimization (Spring quarter 2007)


Miguel Á. Carreira-Perpiñán
Assistant professor
Dept. of Computer Science & Electrical Engineering
OGI School of Science & Engineering / OHSU
miguel-[at]; 503-7481455
Office: Central Building 142

Office hours: by appointment (call or email, including [MATH519] in the subject).

Classes: Mondays and Wednesdays 6:30-7:59pm in classroom 401, Paul Clayton Building (number 2 in the map)

Course web page:

Course description

Optimization problems arise in multiple areas of science, engineering and business. This course introduces numerical methods for continuous optimization, focusing on practical methods. The course will cover derivative-based methods for constrained and unconstrained multivariate optimization, including line-search and trust-region strategies; conjugate-gradient, Newton and quasi-Newton methods; linear programming (simplex and interior-point methods); quadratic programming; penalty, barrier and augmented Lagrangian methods; and sequential quadratic programming. The primary programming tool for this course is Matlab.

Prerequisites: undergraduate courses in linear algebra and multivariate calculus. Basic concepts will be briefly reviewed during the course.


Required textbook (get the errata and additional errata):

There is also a second edition that you can use if you want.

Other recommended books:

All are on reserve in the OGI Library.

If you want to refresh your knowledge of linear algebra and multivariate calculus, the following are helpful (any edition or similar book is fine):

Syllabus and required textbook reading

Before each class, you should have read the corresponding part of the textbook and the notes. I will teach the material in the order below (which is more or less the order in the book) except that the underlined page numbers (corresponding to pages 35-37, 48-52, 62-63 in the notes) will be taught at the end of the course.

Handouts and assignments

Course grading

The course grading will be based on three projects and a final exam, as follows:

While I encourage you to discuss your work with other students, the projects and the exam must be the result of your own work without collaboration.

I will also give homework exercises (mainly from the textbook) of two types, pencil-and-paper and Matlab programming. I will not ask you to solve them, i.e., they will not count towards your grade. I will give the solutions and solve some of the exercises in class. However, I strongly recommend that you try to solve all the exercises on your own.

Optimization links

Matlab tutorials

If you have never used Matlab, there are many online tutorials, for example:

Miguel A. Carreira-Perpinan
Last modified: Sat Jun 9 20:43:25 PDT 2007

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