Re-solving stochastic programming models for airline revenue management
Abstract
We study some mathematical programming formulations for the origin-destination model in airline revenue management. In particular, we focus on the traditional probabilistic model proposed in the literature. The approach we study consists of solving a sequence of two-stage stochastic programs with simple recourse, which can be viewed as an approximation to a multi-stage stochastic programming formulation to the seat allocation problem. Our theoretical results show that the proposed approximation is robust, in the sense that solving more successive two-stage programs can never worsen the expected revenue obtained with the corresponding allocation policy. Although intuitive, such a property is known not to hold for the traditional deterministic linear programming model found in the literature. We also show that this property does not hold for some bid-price policies. In addition, we propose a heuristic method to choose the re-solving points, rather than re-solving at equally-spaced times as customary. Numerical results are presented to illustrate the effectiveness of the proposed approach.
Más información
Título según WOS: | ID WOS:000277783800007 Not found in local WOS DB |
Título de la Revista: | ANNALS OF OPERATIONS RESEARCH |
Volumen: | 177 |
Número: | 1 |
Editorial: | Springer |
Fecha de publicación: | 2010 |
Página de inicio: | 91 |
Página final: | 114 |
DOI: |
10.1007/s10479-009-0603-7 |
Notas: | ISI |