Program Objectives


A principal goal of the OR/IE graduate program is to provide the student with the educational basis for continued learning and to impart the fundamental skills necessary to function effectively as a professional. At the master's level, we strive for a balance of theory and applications, relying heavily on the accumulated years of experience our faculty bring to the classroom. At the PhD level, the emphasis shifts to research, enabling students to extend their field of knowledge and to develop analytic techniques that will serve them in their academic, industrial, or governmental careers. Although rigor is the mainstay at all levels, sufficient flexibility is built into the program to accommodate the needs and interests of most students. With a deep concern for the future, we feel that this formula works best for out students, our faculty, our industrial partners.

Master of Science

In order to be successful at UT Austin and earn your Master's degree while enjoying your time here, you should start planning from the first day in the program. To help you plan, here are some points you will need to remember.

Options
The Graduate Program in OR/IE offers three different Master's degree options:

The Thesis option consists of:
9 hours of required courses,
9 hours of OR/IE courses,
6 hours of courses in your minor area of choice (not OR/IE), and
6 hours of research and thesis writing (ORI 698A and ORI 698B)

The Report option consists of:
9 hours of required courses,
12 to 15 hours of OR/IE courses,
6 hours of courses in your minor area of choice, and
3 hours of research and report writing (ORI 398R)

The Course option consists of:
9 hours of required courses,
15 to 21 hours of OR/IE courses, and
6 hours of courses in your minor area of choice

Note: All students must elect thesis or report option. Those wishing to do all coursework must petition the Graduate Advisor.

Required Courses:
Linear Optimization
Applied Probabilty
Statistical Methods
Note: These core courses must be taken from the OR/IE faculty. If you do not have a background in OR/IE and have never been exposed to OR/IE modeling, you are strongly encouraged to register for our undergraduate course Operations Research Models (ME 366L) during your first year.

Minor Courses:
Upper division undergraduate or graduate courses in other departments are appropriate as supporting courses. These courses must be approved by the Graduate Advisor. Seminar course will not be approved as a supporting course.

Seminar
Seminars have the goal to expand students and faculty knowledge in the field. Every master's student is asked to register for the Seminar course once a year. However, all students are expected to attend every seminar unless conflicts arise.

Doctor of Philosophy

The graduate program in OR/IE expects all doctoral students to go through these three steps:

Qualifying Exam (with written and oral parts, taken typically within the first two years in the program)
Admission to Candidacy (requires the creation of doctoral committee)
Dissertation Defense

Qualifying exam is over two major parts: Deterministic and Stochastic. The following syllabi outline the topics covered in each part of the exam.

Deterministic Part

Stochastic Part

Guidelines
Doctoral students are expected to master the material of a wide range of topics. Students will be required to complete at least 24 credit hours of courses approved by the Graduate Advisor. 

The following 6 core courses will not count towards the 24 credit hours.

ORI 390R Topic 1: Applied Probability
ORI 390R Topic 2: Mathematical Statistics
ORI 390R Topic 5: Applied Stochastic Processes
ORI 391Q Topic 1: Nonlinear Programming
ORI 391Q Topic 4: Integer Programming
ORI 391Q Topic 5: Linear Programming

Mechanical Engineering Department
College of Engineering
The University of Texas at Austin 		Comments or questions:
dmziegler@mail.utexas.edu
Last modified: 25 January 2006