This thesis evaluates the performance of Dynamic Programming (DP) models as applied to airline Revenue Management (RM) compared to traditional Revenue Management models like EMSRb as DP models offer a theoretically attractive alternative to traditional RM models. In the first part of this thesis, we develop a simplified simulator to evaluate the effects of changing demand variance on the performance of standard DP on a single flight leg. This simulator excludes the effects of forecast quality and competitive effects like passenger sell-up and inter-airline spill. In the next part of the thesis, we introduce two network based DP methods that incorporate the network displacement costs in the standard DP based optimizer and perform simulation experiments in a larger competitive network using the Passenger Origin Destination Simulator to study the performance of DP methods in airline Revenue Management systems. The results of single flight leg experiments from the simplified simulator show that DP methods do not consistently outperform EMSRb and the sensitivity analysis show that the performance of DP relative to EMSRb depends on the demand variability, demand factor, fare ratios and passenger arrival pattern. The results from the PODS competitive network simulations show that DP methods, despite not showing any significant benefits in the simplified simulator, can outperform EMSRb when used in a competitive environment because DP's aggressive seat protection policy helps DP generate more revenues than EMSRb due to competitive feedback effects like inter-airline passenger spill-in, and passenger sell-up within the airline.


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    Title :

    Performance of Dynamic Programming methods in airline Revenue Management.
    Performance of DP methods in airline RM


    Contributors:

    Publication date :

    2010


    Size :

    163 pages


    Remarks:

    Thesis (S.M. in Transportation)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering; and, (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2010.
    Cataloged from PDF version of thesis.
    Includes bibliographical references (p. 159-163).


    Type of media :

    Theses


    Type of material :

    Electronic Resource


    Language :

    English




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