Expected Future Value Decomposition Based Bid Price Generation For Large-Scale Network Revenue Management
This paper contributes to the understanding of how firms best set prices. Specifically it studies a multi-stage stochastic programming model for large-scale network revenue management. We solve the model by means of the so-called Expected Future Value (EFV) decomposition via scenario analysis, estimating the impact of the decisions made at a given stage on the objective function value related to the future stages. The EFV curves are used to define bid prices on bundles of resources directly, as opposed to the traditional additive bid prices. Numerical results show that the revenue outcome of our approach is generally comparable to that of state-of-the-art additive approaches, and tends to be better when the network structure is complex. Moreover, our approach requires significantly less computation time than the optimization of the compact representation by plain use of optimization engines.
|Dr. Peter van Baalen|