Dynamic Programming
Course Number: 47840
The objective of this course is to provide an introduction to the theory and applications of dynamic programming (DP). We investigate the theory and methods commonly used in DP. We illustrate their use in solving particular models in various areas, which may include commodity and energy merchant operations, inventory and production management, logistics under uncertainty, real options, and revenue management. We study the concept of recursion, the principle of optimality, basic DP algorithms, their applications to both deterministic and stochastic models in ?nite and in?nite horizon settings, with most of our attention dedicated to Markov decision processes. This course thus features theory, methods, computation, and applications. It provides foundational material for research in reinforcement learning.
Degree: PhD
Concentration: Operations Management
Academic Year: 2023-2024
Semester(s): Mini 2
Required/Elective: Elective
Units: 6