Operations Research

Operations Research (OR) is a scientific approach to problem-solving and decision-making that relies on mathematical modeling, data analysis, and optimization techniques. Its primary goal is to design, manage, and improve complex systems by determining the optimal or most effective allocation of scarce resources. OR is a cornerstone of decision science, supporting industries and sectors ranging from manufacturing and supply chain management to healthcare, public policy, and humanitarian logistics.

The flexibility of OR allows practitioners to focus on either theoretical methodology or practical applications, providing the foundation to tackle real-world challenges. More information about OR and its applications can be found through professional societies like the Institute for Operations Research and the Management Sciences (INFORMS) and the Institute of Industrial & Systems Engineers (IISE).

What do Operations Researchers do?

Operations researchers analyze and optimize complex systems to improve efficiency, performance, and decision-making. They apply tools such as mathematical programming, simulation (e.g., discrete event, Monte Carlo, agent-based), stochastic processes, statistics, probability, queuing theory, network optimization, machine learning, and system science. These methodologies enable them to address challenges in diverse fields like:

Healthcare and medicine: Enhancing patient care, resource allocation, and medical logistics.
Public policy: Shaping data-driven policies for societal impact.
Supply chain and logistics: Streamlining global operations and inventory management.
Manufacturing: Improving production efficiency and minimizing waste.
Telecommunications: Optimizing network infrastructure and service delivery.
Intelligent infrastructure: Managing smart cities and sustainable systems.

By integrating advanced analytics and OR methods, these professionals develop strategies to navigate today’s increasingly interconnected and complex systems.

Graduate Programs in Operations Research

Master's Level	Doctoral Level
M.S. and MEng in Operations Research	Ph.D. in Operations Research

Research in Operations Research

Mathematical Programming (Integer Programming, Stochastic Programming, Mixed-Integer Nonlinear Programming)
Machine Learning; Algorithms
Data-Driven Optimization
Graph and Network Optimization
Simulation modeling
Simulation analysis methodology
Simulation optimization
Uncertainty Quantification
Healthcare and public policy research regarding data analysis, statistics, simulation, optimization, queuing theory
Production, supply chain and logisitcs rsearch regarding optimization, scheduling, delivery, data analysis, homeland security