Operations Research
Operations research is distinguished by its use of quantitative methods (mathematics, statistics and computing) to aid in rational decision making. Operations research has been successfully applied to a wide range of problems arising in business and government, such as locating industrial plants, allocating emergency facilities, planning capital investments, designing communication systems and scheduling production in factories. A common element of these decision problems is the need to allocate scarce resources (such as money, time or space) while attempting to meet conflicting objectives (such as minimizing cost or maximizing production).
Faculty
Faculty involved with operations research include:
- Keisha Cook: modeling complex systems, stochastic processes, Bayesian inference, mathematical statistics, applications in biological sciences.
- Brian Fralix: Queueing theory, applied probability.
- Peter C. Kiessler: Stochastic processes, queueing theory.
- Yuyuan “Lance” Ouyang: Nonlinear optimization, stochastic approximation, algorithm design for big data analytics.
- Matthew J. Saltzman: Computational operations research, mathematical programming.
- Margaret Wiecek: Optimization, multicriteria decision making.
- Boshi Yang: Conic optimization, non-convex quadratically constrained quadratic programming.
Other Resources
Useful Links
Other resources of potential interest include:
-
INFORMS — The Institute for Operations Research and the Management Sciences
-
INFORMS: Educational Programs in OR/MS (login required)
- John Beasley’s OR Notes
Curriculum
Find out more about the curriculum and course descriptions for this interest area.
