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An assessment of the impact of demand management strategies for efficient allocation of airport capacity

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  • Vikrant Vaze
  • Cynthia Barnhart

Abstract

Airport demand management strategies have the potential to mitigate congestion and delays. However, the extent to which the delays can be reduced using such strategies is not clear. In this paper, we develop a bound on the minimum possible level of delays that can be achieved using these strategies. We solve the aggregated timetable development and fleet assignment problem to minimise the system-wide delays assuming a single monopolistic carrier that satisfies all the passenger demand in the USA and maintains the same level-of-service as achieved with the current revenue management practices of individual carriers. The problem is formulated as a large-scale, integer linear programming model and solved using linear programming relaxation and heuristics. A network delay simulator is used for calculating the delays under different capacity scenarios. The results indicate the large inefficiencies in the usage of airport infrastructure in the domestic US caused by competitive airline scheduling decisions.

Suggested Citation

  • Vikrant Vaze & Cynthia Barnhart, 2012. "An assessment of the impact of demand management strategies for efficient allocation of airport capacity," International Journal of Revenue Management, Inderscience Enterprises Ltd, vol. 6(1/2), pages 5-27.
    • Handle: RePEc:ids:ijrevm:v:6:y:2012:i:1/2:p:5-27
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    References listed on IDEAS

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    Cited by:

    1. Cavusoglu, Sabriye Sera & Macário, Rosário, 2021. "Minimum delay or maximum efficiency? Rising productivity of available capacity at airports: Review of current practice and future needs," Journal of Air Transport Management, Elsevier, vol. 90(C).
    2. Lin, Ming Hsin & Zhang, Anming, 2016. "Hub congestion pricing: Discriminatory passenger charges," Economics of Transportation, Elsevier, vol. 5(C), pages 37-48.
    3. Gillen, David & Jacquillat, Alexandre & Odoni, Amedeo R., 2016. "Airport demand management: The operations research and economics perspectives and potential synergies," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 495-513.
    4. Liu, Wenjing & Zhao, Qiuhong & Delahaye, Daniel, 2022. "Research on slot allocation for airport network in the presence of uncertainty," Journal of Air Transport Management, Elsevier, vol. 104(C).
    5. Vikrant Vaze & Cynthia Barnhart, 2012. "Modeling Airline Frequency Competition for Airport Congestion Mitigation," Transportation Science, INFORMS, vol. 46(4), pages 512-535, November.
    6. Dixit, Aasheesh & Kumar, Patanjal & Jakhar, Suresh Kumar, 2022. "Effectiveness of carbon tax and congestion cost in improving the airline industry greening level and welfare: A case of two competing airlines," Journal of Air Transport Management, Elsevier, vol. 100(C).
    7. Jacquillat, Alexandre & Odoni, Amedeo R., 2018. "A roadmap toward airport demand and capacity management," Transportation Research Part A: Policy and Practice, Elsevier, vol. 114(PA), pages 168-185.

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