Article ID: | iaor20161167 |
Volume: | 15 |
Issue: | 2 |
Start Page Number: | 107 |
End Page Number: | 137 |
Publication Date: | Apr 2016 |
Journal: | Journal of Revenue and Pricing Management |
Authors: | Karaesmen Fikri, Klabjan Diego, Shebalov Sergey, Seng Pun Chan |
Keywords: | transportation: air, programming: dynamic, combinatorial optimization, heuristics, simulation |
In order to accept future high‐yield booking requests, airlines protect seats from low‐yield passengers. More seats may be reserved when passengers faced with closed fare classes can upsell to open higher fare classes. We address the airline revenue management problem with capacity nesting and customer upsell, and formulate this problem by a stochastic optimization model to determine a set of static protection levels for each itinerary. We apply an approximate dynamic programming framework to approximate the objective function by piecewise linear functions, whose slopes (marginal revenue) are iteratively updated and returned by an efficient heuristic that simultaneous handles both nesting and upsells. The resulting allocation policy is tested over a real airline network and benchmarked against the randomized linear programming bid‐price policy under various demand settings. Simulation results suggest that the proposed allocation policy significantly outperforms when incremental demand or upsell probability are high. Structural analyses are also provided for special demand dependence cases.