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261. Robust optimization models for single-leg and network airline revenue management
Invited abstract in session TA-26: Applications to Logistics and Transportation, stream Combinatorial Optimization.
Tuesday, 8:30-10:00Room: 012 (building: 208)
Authors (first author is the speaker)
| 1. | Mustafa Pinar
|
| Department of Industrial Engineering, Bilkent University | |
| 2. | Irem Bahtiyar
|
| Bilkent University | |
| 3. | Ali Eren Demir
|
| Bilkent University | |
| 4. | Itir Karaesmen
|
| Kogod School of Business, American University |
Abstract
Effective capacity allocation methods play crucial roles in Revenue Management. Yet, current methods for determining optimal capacity controls under uncertainties, such as stochastic optimization, often assume a known distribution for unknown parameters. This assumption may degrade the model’s performance when faced with unexpected data patterns. This paper explores a novel approach through robust optimization formulations for addressing stochastic resource allocation problems. We introduce heuristics 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 significantly improved worst-case performances. Notably, even under favorable scenarios, our solutions remain comparable to existing methods in the revenue management literature.
Keywords
- Airline Applications
- Programming, Linear
- Robust Optimization
Status: accepted
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