Operations Research is the study of mathematical models and algorithms for optimal decision making. It is a core discipline of data analytics, which is the process of turning raw data into knowledge, insights, and better decisions. The Operations Research group at the Tepper School studies theory, methodology, algorithms, and applications related to the entire pipeline from data to decisions.
Specific research topics include linear and nonlinear integer programming, constraint programming, convex optimization, combinatorial optimization, approximation and online algorithms, scheduling, machine learning, data mining, large data analysis, and ethics of artificial intelligence.
Application domains include network design, bioinformatics, vehicle routing, financial portfolio optimization, large-scale server load balancing, drug discovery, and personalized medicine.
Our faculty members have won prestigious awards, including National Science Foundation CAREER awards, National Academy of Engineering membership, the Lanchester Prize, the Fulkerson Prize, the Dantzig Prize, the Von Neumann Prize, the Khachiyan Prize, the Franz Edelman Award, the George E. Kimball Medal, the INFORMS Computing Society Prize, the INFORMS Optimization Society Young Researchers Prize, and numerous best paper awards.
Faculty Research Spotlight
In our Academic Minds video series, our faculty share insights from their research on wide-ranging business topics.
How Can We Better Extract Answers from Big Data?
Ben Moseley, Assistant Professor of Operations Research
How to Keep Inventory Balanced in the Bike Sharing Economy
Willem-Jan van Hoeve, Carnegie Bosch Associate Professor of Operations Research
Operations Research Faculty in the News
Using Analytics To Improve IT Operations and Services, featuring Ben Moseley, Assistant Professor of Operations Research.
Peter Thiel Said That AI Is a Military Technology That Will Primarily Be Used 'by Generals,' but Experts Say That View Is Too Pessimistic, featuring Fatma Kilinc-Karzan, Associate Professor of Operations Research.
Recent Faculty Publications
- “Incorporating Black-Litterman Views in Portfolio Construction when Stock Returns are a Mixture of Normals” by Kocuk, B., Cornuejols, G. (2021) in Omega
- “The Generalized Trust Region Subproblem: Solution Complexity and Convex Hull Results” by Alex L. Wang, A. L.,, Kilinc-Karzan, F. (2020) in Mathematical Programming
- “Online Scheduling via Learned Weights” by Lattanzi, S., Lavastida, T., Moseley, B., Vassilvitskii, S. (2020) in Proceedings of the 2020 ACM-SIAM Symposium on Discrete Algorithms (SODA)
- “The Condition Number of a Function Relative to a Set” Gutman, D.H., Peña, J.F. (2021) in Mathematical Programming