Re-solving stochastic programming models for airline revenue management

Chen, Lijian; Homem-de-Mello, Tito

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