Robust Optimization Models for Network Revenue Management by İrem Bahtiyar
Thesis Advisor: Prof. Dr. Mustafa Çelebi Pınar
Date: July 9 Tuesday 2024
Time: 16.00
Place: Zoom
This is an online seminar. To obtain event details please send a message to department.
Abstract:
Effective capacity allocation methods play a crucial role in Network Revenue Management. Yet, current methods for determining optimal capacity controls under uncertainty, such as stochastic optimization, often assume a known probability distribution for unknown parameters.
This assumption may degrade a model’s performance when faced with unexpected data patterns. This thesis explores a novel approach through robust optimization to address stochastic resource allocation problems.
We introduce a heuristic based on these robust formulations to derive actionable results. Through extensive simulations focused on seat allocation problems within the revenue management domain, our proposed formulations demonstrate improved worst-case performances. Notably, even under favorable scenarios, our solutions remain comparable to existing methods in the revenue management literature.