Re-solving stochastic programming models for airline revenue management

Lijian Chen, Tito Homem-de-Mello

Producción científica: Contribución a una revistaArtículorevisión exhaustiva

32 Citas (Scopus)

Resumen

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.

Idioma originalInglés
Páginas (desde-hasta)91-114
Número de páginas24
PublicaciónAnnals of Operations Research
Volumen177
N.º1
DOI
EstadoPublicada - 2010
Publicado de forma externa

Huella

Profundice en los temas de investigación de 'Re-solving stochastic programming models for airline revenue management'. En conjunto forman una huella única.

Citar esto