Decision Making Under Uncertainty


Units: 6


This course provides an introduction to modeling and computational methods used by policy- makers, managers and analysts to support decision-making. The first half of the course focuses on deterministic optimization, and covers linear programming, network optimization and integer programming. The second half of this course introduces risk and uncertainty, and includes methods to characterize uncertainty and methods to optimize decisions under uncertainty.

Learning Outcomes

1. Become facile with Excel. This helps you get a job.
2. Survey many optimization and decision science methods. This helps you hire consultants
intelligently, should you need to.
3. Learn some analytical methods. This helps you solve smaller problems yourself.
4. Learn how to make a mathematical model. This helps you think clearly and precisely, especially
for industrial-sized problems.

Prerequisites Description

A first course in statistics is required, such as either 95-796 or 90-711.