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Endogenous control of service rates in stochastic and dynamic queuing models of airport congestion

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  • Jacquillat, Alexandre
  • Odoni, Amedeo R.

Abstract

Airport congestion mitigation requires reliable delay estimates. This paper presents an integrated model of airport congestion that combines a tactical model of capacity utilization into a strategic queuing model. The model quantifies the relationships between flight schedules, airport capacity and flight delays, while accounting for the way arrival and departure service rates can be controlled over the day to maximize operating efficiency. We show that the model estimates the average and variability of the delays observed at New York’s airports relatively well. Results suggest that delays can be extremely sensitive to even small changes in flight schedules or airport capacity.

Suggested Citation

  • Jacquillat, Alexandre & Odoni, Amedeo R., 2015. "Endogenous control of service rates in stochastic and dynamic queuing models of airport congestion," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 73(C), pages 133-151.
  • Handle: RePEc:eee:transe:v:73:y:2015:i:c:p:133-151
    DOI: 10.1016/j.tre.2014.10.014
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    References listed on IDEAS

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    1. Liu, Pei-chen Barry & Hansen, Mark & Mukherjee, Avijit, 2008. "Scenario-based air traffic flow management: From theory to practice," Transportation Research Part B: Methodological, Elsevier, vol. 42(7-8), pages 685-702, August.
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    4. Swaroop, Prem & Zou, Bo & Ball, Michael O. & Hansen, Mark, 2012. "Do more US airports need slot controls? A welfare based approach to determine slot levels," Transportation Research Part B: Methodological, Elsevier, vol. 46(9), pages 1239-1259.
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    Citations

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    Cited by:

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    2. Schwarz, Justus Arne & Selinka, Gregor & Stolletz, Raik, 2016. "Performance analysis of time-dependent queueing systems: Survey and classification," Omega, Elsevier, vol. 63(C), pages 170-189.
    3. Li, Max Z. & Ryerson, Megan S., 2019. "Reviewing the DATAS of aviation research data: Diversity, availability, tractability, applicability, and sources," Journal of Air Transport Management, Elsevier, vol. 75(C), pages 111-130.
    4. Olivares, Felipe & Sun, Xiaoqian & Wandelt, Sebastian & Zanin, Massimiliano, 2023. "Measuring landing independence and interactions using statistical physics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 170(C).
    5. Ng, K.K.H. & Lee, C.K.M. & Chan, Felix T.S. & Qin, Yichen, 2017. "Robust aircraft sequencing and scheduling problem with arrival/departure delay using the min-max regret approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 106(C), pages 115-136.
    6. Ribeiro, Nuno Antunes & Jacquillat, Alexandre & Antunes, António Pais & Odoni, Amedeo, 2019. "Improving slot allocation at Level 3 airports," Transportation Research Part A: Policy and Practice, Elsevier, vol. 127(C), pages 32-54.

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