90-722 Optimization & Decision Modeling for Policy
12 units, Carnegie Mellon University
Optimization & Decision Modeling for Policy (previously Management Science I and II) is an introductory course in analytics and management science that surveys a variety of hands-on quantitative and modeling methods useful to decision makers and analysts. We will develop a practical toolkit for solving real-world decision-making problems. The first part of the course focuses on optimization models and methods. Optimization models provide a quantitative framework to guide decisions when you want to maximize (or minimize) some outcome, subject to various requirements. This applies to nearly any industry, such as booking patients for surgery to minimize wait times under schedule constraints, or allocating limited aid resources across a community to maximize impact. The second half of the course will introduce methods for decision-making under uncertainty. We will cover various forecasting methods (qualitative, time-series, categorical) to project what might happen in the future, and we will then introduce methods to make better decisions in the face of uncertainty (simulation and optimization). By the end of the class, you will be able to translate real-world problems into mathematical formulations, solve them using Excel, and interpret the solutions. This skill will be a significant asset on the job market and in your career.
Prerequisites: none listed
Offered: Spring 2027, Spring 2026
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