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Solving for an optimal airline yield management policy via statistical learning

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  • Victoria C. P. Chen
  • Dirk Günther
  • Ellis L. Johnson

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.

Suggested Citation

  • Victoria C. P. Chen & Dirk Günther & Ellis L. Johnson, 2003. "Solving for an optimal airline yield management policy via statistical learning," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 52(1), pages 19-30, January.
    • Handle: RePEc:bla:jorssc:v:52:y:2003:i:1:p:19-30
    DOI: 10.1111/1467-9876.00386
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    Cited by:

    1. Alec Morton, 2006. "Structural properties of network revenue management models: An economic perspective," Naval Research Logistics (NRL), John Wiley & Sons, vol. 53(8), pages 748-760, December.
    2. Dachuan Shih & Seoung Kim & Victoria Chen & Jay Rosenberger & Venkata Pilla, 2014. "Efficient computer experiment-based optimization through variable selection," Annals of Operations Research, Springer, vol. 216(1), pages 287-305, May.
    3. Pilla, Venkata L. & Rosenberger, Jay M. & Chen, Victoria & Engsuwan, Narakorn & Siddappa, Sheela, 2012. "A multivariate adaptive regression splines cutting plane approach for solving a two-stage stochastic programming fleet assignment model," European Journal of Operational Research, Elsevier, vol. 216(1), pages 162-171.
    4. Elcin Koc & Cem Iyigun, 2014. "Restructuring forward step of MARS algorithm using a new knot selection procedure based on a mapping approach," Journal of Global Optimization, Springer, vol. 60(1), pages 79-102, September.

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