Optimizing Revenue Maximization and Demand Learning in Airline Revenue Management
Correctly estimating how demand respond to prices is fundamental for airlines willing to optimize their pricing policy. Under some conditions, these policies, while aiming at maximizing short term revenue, can present too little price variation which may decrease the overall quality of future demand forecasting. This problem, known as earning while learning problem, is not exclusive to airlines, and it has been investigated by academia and industry in recent years. One of the most promising methods presented in literature combines the revenue maximization and the demand model quality into one single objective function. This method has shown great success in simulation studies and real life benchmarks. Nevertheless, this work needs to be adapted to certain constraints that arise in the airline revenue management (RM), such as the need to control the prices of several active flights of a leg simultaneously. In this paper, we adjust this method to airline RM while assuming unconstrained capacity. Then, we show that our new algorithm efficiently performs price experimentation in order to generate more revenue over long horizons than classical methods that seek to maximize revenue only.
Code (0)
등록된 구현이 없습니다.
Tasks
Demand ForecastingManagementSimilar Papers 제목 키워드 기반
Autonomous Airline Revenue Management: A Deep Reinforcement Learning Approach to Seat Inventory Control and Overbooking
Revenue management can enable airline corporations to maximize the revenue generated from each scheduled flight departing in their transportation network by means of finding the optimal policies for differential pricing,…
Deep Reinforcement LearningManagementQ-LearningReinforcement LearningA machine learning approach to itinerary-level booking prediction in competitive airline markets
Demand forecasting is extremely important in revenue management. After all, it is one of the inputs to an optimisation method which aim is to maximize revenue. Most, if not all, forecasting methods use historical data to…
BIG-bench Machine LearningDemand ForecastingManagementTime Series+1AI-CARGO: A Data-Driven Air-Cargo Revenue Management System
We propose AI-CARGO, a revenue management system for air-cargo that combines machine learning prediction with decision-making using mathematical optimization methods. AI-CARGO addresses a problem that is unique to the ai…
Decision MakingManagementStochastic OptimizationData-Driven Revenue Management for Air Cargo
It is well-recognized that Air Cargo revenue management is quite different from its passenger airline counterpart. Inherent demand volatility due to short booking horizon and lumpy shipments, multi-dimensionality and unc…
ManagementEstimating the Gains (and Losses) of Revenue Management
Despite the wide adoption of revenue management in many industries such as airline, railway, and hospitality, there is still scarce empirical evidence on the gains or losses of such strategies compared to uniform pricing…
Management