Operations Research
Operations Research is the branch of applied mathematics concerned with applying analytical
methods to help make better management decisions. Operations research is also known
as management science and industrial engineering. Operations researchers build mathematical
models and apply optimization, simulation, and other mathematical tools to analyze
complex situations. Operations Research is used in a wide range of industries, from
telecommunication to health care to financial services.
The Stony Brook Department of Applied Mathematics and Statistics has a program of
graduate training and research in Operations Research, offering M.S. and Ph.D. degrees
as well as a 18-credit Advanced Certificate in Operations Research. In addition to faculty in Applied Mathematics, the Operations Research program also
draws upon faculty in Computer Science, Economics, and the College of Business.
Research interests of operations research faculty cover a range of problems in discrete
and stochastic optimization: smart energy grids, forecasting electric demand, efficient
manufacturing, routing aircraft around storm systems, robotics, geographical information
systems, recursive learning automata, and efficient design of clinical trials. For
more information about Operations Research research, see Operations Research projects.
The standard professional degree for operations researchers working in business and industry is the M.S. degree. The department offers a 30-credit M.S. degree, with no thesis, that follows the guidelines for professional training of the operations research society INFORMS. The department also offers a Ph.D. degree which starts off with the same courses as the M.S. degree. For more details about requirements for the Ph.D., please see Ph.D. Requirements.
Required Courses for M.S. Degree in Operations Research Track
- AMS 507 Introduction to Probability
- AMS 510 Analytical Methods for Applied Mathematics and Statistics
- AMS 540 Linear Programming
- AMS 550 Stochastic Models
- AMS 553/CSE 529 Simulation and Modeling
- AMS 595 Fundamentals of Computing
- One course in statistics (courses numbered AMS 570-586)
plus three electives from the following selection of courses
- AMS 542/CSE 548 Analysis of Algorithms
- AMS 544 Discrete and Nonlinear Optimization
- AMS 545 Computational Geometry
- AMS 546 Network Flows
- AMS 547 Discrete Mathematics
- AMS 552 Game Theory
- AMS 554 Queuing Theory
- AMS 555 Game Theory II
- AMS 556 Dynamic Programming
- AMS 559 Smart Energy in the Information Age
- AMS 560 Big Data Systems, Algorithms and Networks
- AMS 569 Probability Theory I
- ESE 533 Convex Optimization and Engineering Applications
- One additional course in statistics (AMS 570-AMS 586)
- One course in quantitative finance (AMS 511-AMS 523)
A recommended course sequence is as follows:
First Semester (Fall):
- AMS 507 Introduction to Probability
- AMS 510 Analytical Methods for Applied Mathematics and Statistics
- AMS 540 Linear Programming
- AMS 595 Fundamentals of Computing
Second Semester (Spring):
- AMS 550 Stochastic Models
- One Operations Research Elective
- One Statistics Elective
Third Semester (Fall):
- AMS 553 Simulation and Modeling
- Two electives (Operations Research)