Network Bid-price Control under Generalized Attraction Model

In recent years, the integration of discrete choice models and revenue management has attracted growing attention from both academia and the industry. In this study, we focus on airline network revenue management with a bid-price control under the Generalized Attraction Model (GAM), an extension of the well-known multinomial logit model. We prove that the GAM has a nested efficient frontier, a property that enables the implementation of a network bid-price control policy through a technique known as fare transformation. We also propose a fast algorithm to identify a nested efficient frontier, which significantly reduces the complexity and enhances the practicality of the GAM. Last but not least, we explore the mixture model of independent demand and GAM. We prove that this mixture model also has a nested efficient frontier, which can be tackled by a parametric linear program.