My Master Thesis on Approximate Dynamic Programming
Approximate Dynamic Programming as a technique is used in many fields including Revenue Management. In my master thesis, I want to explore different methods used in the field and in academia. Guided by various papers, I will implement the procedures and analyze them on various performance measures.
The papers to be considered include:
- Koch, Least squares approximate policy iteration for learning bid prices in choice-based revenue management
- Bront, A Column Generation Algorithm for Choice-Based Network Revenue Management