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Landings at Logan Airport: Describing and Increasing Airport Capacity

Author

Listed:
  • C. S. Venkatakrishnan

    (Decision Focus Incorporated, Mountain View, California 94041)

  • Arnold Barnett

    (Massachusetts Institute of Technology, Cambridge, Massachusetts 02139)

  • Amedeo R. Odoni

    (Massachusetts Institute of Technology, Cambridge, Massachusetts 02139)

Abstract

To understand how greatly new computer-based Decision Support Systems can benefit air traffic control, we study air traffic delays for landing aircraft at Boston. First, we develop an empirical model for present day Landing Time Intervals (LTIs) between aircraft in terms of two factors that significantly affect them: the landing runway configuration and the weight-class categories of the aircraft. Next, we develop three increasingly rich models of Boston's terminal airspace and apply, on airflow data, sequencing algorithms meant to expedite the landing of incoming aircraft. Comparing sequences suggested by the algorithms to those now used by controllers, we estimate that better sequencing can reduce delays by 30% in some instances. However, such improvements must be balanced against the effects such algorithms would have on workloads and other aspects of the air traffic control environment.

Suggested Citation

  • C. S. Venkatakrishnan & Arnold Barnett & Amedeo R. Odoni, 1993. "Landings at Logan Airport: Describing and Increasing Airport Capacity," Transportation Science, INFORMS, vol. 27(3), pages 211-227, August.
    • Handle: RePEc:inm:ortrsc:v:27:y:1993:i:3:p:211-227
    DOI: 10.1287/trsc.27.3.211
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    Cited by:

    1. Lieder, Alexander & Briskorn, Dirk & Stolletz, Raik, 2015. "A dynamic programming approach for the aircraft landing problem with aircraft classes," European Journal of Operational Research, Elsevier, vol. 243(1), pages 61-69.
    2. Xiao, Mei & Chien, Steven & Schonfeld, Paul & Hu, Dawei, 2020. "Optimizing flight equencing and gate assignment considering terminal configuration and walking time," Journal of Air Transport Management, Elsevier, vol. 86(C).
    3. Kim, Amy & Hansen, Mark, 2013. "Deconstructing delay: A non-parametric approach to analyzing delay changes in single server queuing systems," Transportation Research Part B: Methodological, Elsevier, vol. 58(C), pages 119-133.
    4. Ahmed Ghoniem & Hanif D. Sherali & Hojong Baik, 2014. "Enhanced Models for a Mixed Arrival-Departure Aircraft Sequencing Problem," INFORMS Journal on Computing, INFORMS, vol. 26(3), pages 514-530, August.
    5. J E Beasley & M Krishnamoorthy & Y M Sharaiha & D Abramson, 2004. "Displacement problem and dynamically scheduling aircraft landings," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(1), pages 54-64, January.
    6. Dixit, Aasheesh & Jakhar, Suresh Kumar, 2021. "Airport capacity management: A review and bibliometric analysis," Journal of Air Transport Management, Elsevier, vol. 91(C).
    7. Balliauw, Matteo & Onghena, Evy, 2020. "Expanding airport capacity of cities under uncertainty: Strategies to mitigate congestion," Journal of Air Transport Management, Elsevier, vol. 84(C).
    8. Ghoniem, Ahmed & Farhadi, Farbod & Reihaneh, Mohammad, 2015. "An accelerated branch-and-price algorithm for multiple-runway aircraft sequencing problems," European Journal of Operational Research, Elsevier, vol. 246(1), pages 34-43.
    9. A R Brentnall & R C H Cheng, 2009. "Some effects of aircraft arrival sequence algorithms," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(7), pages 962-972, July.
    10. Schank, Joshua L., 2005. "Solving airside airport congestion: Why peak runway pricing is not working," Journal of Air Transport Management, Elsevier, vol. 11(6), pages 417-425.
    11. G. Guadagni & S. Ndreca & B. Scoppola, 2011. "Queueing systems with pre-scheduled random arrivals," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 73(1), pages 1-18, February.
    12. J. E. Beasley & M. Krishnamoorthy & Y. M. Sharaiha & D. Abramson, 2000. "Scheduling Aircraft Landings—The Static Case," Transportation Science, INFORMS, vol. 34(2), pages 180-197, May.

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