Operations Research

How do you make a complex system more efficient, reliable or effective? Operations research uses mathematics, data and computational methods to help answer that question. Operations research evaluates complex systems to make better decisions. You’ll learn to turn real-world challenges into mathematical models and use those models to identify practical solutions.

Program Overview

The Operations Research minor supplements your engineering or applied science major with a formal approach to mathematical modeling and decision-making.  

You’ll develop skills in optimization, decision analysis, stochastic modeling and simulation and learn how these methods can be used to assess and improve engineered systems. Applications can range from manufacturing and mining to energy, mechanical systems, wastewater treatment and chemical processes.  

Operations research is highly interdisciplinary at Mines, with faculty applying these methods across engineering, mathematics, computer science, economics and business.

Program Options

The 18-credit minor gives you flexibility to build a sequence of courses that complements your major and interests. Your coursework will include both deterministic modeling, which examines systems with certain inputs and relationships, and stochastic modeling, which incorporates uncertainty and probability.  

You can explore subjects such as linear and nonlinear optimization, artificial intelligence, algorithms, statistical modeling, simulation, decision analytics, supply chain analytics, and mine systems analysis.  

Only three credits may come from your degree-granting department, encouraging you to build an interdisciplinary program of study. 

Major/minor pairings

• Mechanical Engineering: Apply optimization and modeling to manufacturing, energy systems, equipment, scheduling and other complex engineering operations.
• Mining Engineering: Use operations research to address challenges such as mine design, production scheduling, logistics and resource allocation.
• Computer Science: Combine computing and algorithms with mathematical optimization, simulation and data-driven decision-making.