Solving for an Optimal Airline Yield Management Policy via Statistical Learning

Victoria C. P. Chen · Ellis L. Johnson

37 citations0/0 files storedJournal of the Royal Statistical Society Series C (Applied Statistics)

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Supply Chain and Inventory Management Aviation Industry Analysis and Trends Air Traffic Management and Optimization

Abstract

Summary The yield management (YM) problem considers the task of maximizing a company's revenue. For the competitive airline industry, profit margins depend on a good YM policy. Research on airline YM is abundant but still limited to heuristics and small cases. We address the YM problem for a major domestic airline carrier's hub-and-spoke network, involving 20 cities and 31 flight legs. This is a problem of realistic size since airline networks are usually separated by hub cities. Our method is a variant of the orthogonal array experimental designs and multivariate adaptive regression splines stochastic dynamic programming method. Our method is demonstrated to outperform state of the art YM methods.

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References

1999Revenue Management: Research Overview and Prospects 1998An Analysis of Bid-Price Controls for Network Revenue Management 1999Airline Yield Management with Overbooking, Cancellations, and No-Shows 1995An Application of Yield Management to the Hotel Industry Considering Multiple Day Stays 1999The Underlying Markov Decision Process in the Single-Leg Airline Yield-Management Problem 1999A Randomized Linear Programming Method for Computing Network Bid Prices 1992Airline network seat inventory control : methodologies and revenue impacts 1982The Passenger-Mix Problem in the Scheduled Airlines

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