A revenue management system which can learn by itself

Most traditional revenue management systems do not directly learn from past mistakes in setting future inventory control policies. Instead, these systems rely on feedback loops created by forecasting and optimisation models and the resulting impacts on observed passenger behaviour. In this paper, we propose to apply the concept of ‘reinforcement learning’, borrowed from the field of industrial engineering, to create a revenue management system that can learn as it goes.