IE 2086 - DECISION MODELS

Minimum Credits: 3
Maximum Credits: 3
Decision making under uncertainty is the key to understanding a variety of problems from industry, including inventory control, revenue management, energy, healthcare, and logistics. This course covers the fundamentals of stochastic (sequential) decision models, including data-driven and risk-averse methods, with applications to real-world problems.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad Letter Grade
Course Requirements: CREQ: IE 2005; PROG: Swanson School of Engineering

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