Aviation Data Analysis by Linear Programming in Airline Network Revenue Management

  • Wolfgang GaulEmail author
  • Christoph Winkler
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)


Aviation data comprise, e.g., bookings and cancellations by consumers as well as no show situations before departure, aircraft-type assignments to flight legs and overbooking-decisions to avoid empty seats in airplanes. Here deterministic linear programming (DLP) is a widely used approach to process this kind of data in an area called airline network revenue management for which adaptions of a basic DLP-model to overbooking situations as well as the offering of flexible products are known. We combine these concepts in a model which simultaneously allows the incorporation of overbooking-decisions and the offering of specific as well as flexible products. Additionally, we further extend this integrated formulation to allow the treatment of different booking-classes and aircraft-type assignment considerations. We present characteristics of the new approach, which uses the overlapping science directions of data analysis and operations research, point out differences to already known results in airline network revenue management, describe an example which illustrates how the different aspects can be considered, and indicate the advantages of our model in view of various data settings.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Karlsruhe Institute of Technology (KIT)KarlsruheGermany

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