Choice-based EMSR methods for single-leg revenue management with demand dependencies

Revenue management (RM) based on customer choice models has gained interest in the 21st century. Changes in airline distribution strategies and improvements in online search engines have resulted in fierce competition, fare transparency and greater usage of restriction-free pricing. Existing solutions to RM with restriction-free pricing have proven ineffective and use either ad hoc adjustments to traditional capacity allocation or computationally intensive dynamic programming. We present new generalised EMSR formulations for the single-leg, nested, multiple fare RM problem that work in both restriction-free and traditional airfare conditions. In our framework, demand for different fare classes is estimated by a customer choice model. We show how a multinomial logit demand model can provide upsell estimates for handling dependent demands and also account for competitive effects. We develop efficient and nearly optimal static heuristics for RM optimisation that are more general and provide better performance than the widely used EMSR-b algorithm for independent demands. Variations of the algorithm for both low-to-high and mixed arrival order cases are provided.