IDEAS home Printed from https://ideas.repec.org/a/inm/ortrsc/v50y2016i1p94-109.html
   My bibliography  Save this article

A Queuing Model of the Airport Departure Process

Author

Listed:
  • Ioannis Simaiakis

    (Massachusetts Institute of Technology, Cambridge, Massachusetts 02139)

  • Hamsa Balakrishnan

    (Massachusetts Institute of Technology, Cambridge, Massachusetts 02139)

Abstract

This paper presents an analytical model of the aircraft departure process at an airport. The modeling procedure includes the estimation of unimpeded taxi-out time distributions and the development of a queuing model of the departure runway system based on the transient analysis of D / E /1 queuing systems. The parameters of the runway service process are estimated using operational data. Using the aircraft pushback schedule as input, the model predicts the expected runway schedule and takeoff times. It also estimates the expected taxi-out time, queuing delay, and its variance for each flight in addition to the congestion level of the airport, sizes of the departure runway queues, and the departure throughput. The proposed approach is illustrated using a case study based on Newark Liberty International Airport. The model is trained using data from 2011 and is subsequently used to predict taxi-out times in 2007 and 2010. The predictions are compared with actual data to demonstrate the predictive capabilities of the model.

Suggested Citation

  • Ioannis Simaiakis & Hamsa Balakrishnan, 2016. "A Queuing Model of the Airport Departure Process," Transportation Science, INFORMS, vol. 50(1), pages 94-109, February.
    • Handle: RePEc:inm:ortrsc:v:50:y:2016:i:1:p:94-109
    DOI: 10.1287/trsc.2015.0603
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/trsc.2015.0603
    Download Restriction: no
    File URL: https://libkey.io/10.1287/trsc.2015.0603?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Bernard O. Koopman, 1972. "Air-Terminal Queues under Time-Dependent Conditions," Operations Research, INFORMS, vol. 20(6), pages 1089-1114, December.
    2. David J. Hand & Heikki Mannila & Padhraic Smyth, 2001. "Principles of Data Mining," MIT Press Books, The MIT Press, edition 1, volume 1, number 026208290x, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Martina Zámková & Stanislav Rojík & Martin Prokop & Radek Stolín, 2022. "Factors Affecting the International Flight Delays and Their Impact on Airline Operation and Management and Passenger Compensations Fees in Air Transport Industry: Case Study of a Selected Airlines in ," Sustainability, MDPI, vol. 14(22), pages 1-16, November.
    2. Chen, Shuiwang & Wu, Lingxiao & Ng, Kam K.H. & Liu, Wei & Wang, Kun, 2024. "How airports enhance the environmental sustainability of operations: A critical review from the perspective of Operations Research," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 183(C).
    3. Chandra, Aitichya & Verma, Ashish & Sooraj, K.P. & Padhi, Radhakant, 2023. "Modelling and assessment of the arrival and departure process at the terminal area: A case study of Chennai international airport," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    4. Pérez-Castán, Javier A. & Asensio, Beatriz & Rodríguez-Sanz, à lvaro & Ho-Huu, Vinh & Sanz, Luis Pérez & Comendador, Fernando Gómez & Valdés, Rosa M.Arnaldo, 2020. "Impact of Continuous Climb Operations in ATC workload. Case-study Palma airport," Journal of Air Transport Management, Elsevier, vol. 89(C).
    5. Li, Chi & Mao, Jianfeng & Li, Lingyi & Wu, Jingxuan & Zhang, Lianmin & Zhu, Jianyu & Pan, Zibin, 2024. "Flight delay propagation modeling: Data, Methods, and Future opportunities," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 185(C).
    6. Birolini, Sebastian & Jacquillat, Alexandre, 2023. "Day-ahead aircraft routing with data-driven primary delay predictions," European Journal of Operational Research, Elsevier, vol. 310(1), pages 379-396.
    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.
    8. Tang, Nga Yung Agnes & Wu, Cheng-Lung & Tan, David, 2020. "Evaluating the implementation of performance-based fuel uplift regulation for airline operation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 133(C), pages 47-61.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Shone, Rob & Glazebrook, Kevin & Zografos, Konstantinos G., 2019. "Resource allocation in congested queueing systems with time-varying demand: An application to airport operations," European Journal of Operational Research, Elsevier, vol. 276(2), pages 566-581.
    2. Le, Hong Hanh & Viviani, Jean-Laurent, 2018. "Predicting bank failure: An improvement by implementing a machine-learning approach to classical financial ratios," Research in International Business and Finance, Elsevier, vol. 44(C), pages 16-25.
    3. Li, Hui & Sun, Jie, 2009. "Hybridizing principles of the Electre method with case-based reasoning for data mining: Electre-CBR-I and Electre-CBR-II," European Journal of Operational Research, Elsevier, vol. 197(1), pages 214-224, August.
    4. Min-feng Lee & Guey-shya Chen & Shao-pin Lin & Wei-jie Wang, 2022. "A Data Mining Study on House Price in Central Regions of Taiwan Using Education Categorical Data, Environmental Indicators, and House Features Data," Sustainability, MDPI, vol. 14(11), pages 1-15, May.
    5. Caruso, Germán & Scartascini, Carlos & Tommasi, Mariano, 2015. "Are we all playing the same game? The economic effects of constitutions depend on the degree of institutionalization," European Journal of Political Economy, Elsevier, vol. 38(C), pages 212-228.
    6. M. Almiñana & L. Escudero & A. Pérez-Martín & A. Rabasa & L. Santamaría, 2014. "A classification rule reduction algorithm based on significance domains," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(1), pages 397-418, April.
    7. Silvia Figini & Ron Kenett & SILVIA SALINI, 2010. "Integrating Operational and Financial Risk Assessments," UNIMI - Research Papers in Economics, Business, and Statistics unimi-1099, Universitá degli Studi di Milano.
    8. Onur Doğan & Hakan Aşan & Ejder Ayç, 2015. "Use Of Data Mining Techniques In Advance Decision Making Processes In A Local Firm," European Journal of Business and Economics, Central Bohemia University, vol. 10(2), pages 6821:10-682, January.
    9. Patricia E. N. Lutu & Andries P. Engelbrecht, 2013. "Base Model Combination Algorithm for Resolving Tied Predictions for K -Nearest Neighbor OVA Ensemble Models," INFORMS Journal on Computing, INFORMS, vol. 25(3), pages 517-526, August.
    10. Adrien Jamain & David Hand, 2008. "Mining Supervised Classification Performance Studies: A Meta-Analytic Investigation," Journal of Classification, Springer;The Classification Society, vol. 25(1), pages 87-112, June.
    11. Ali Yousefi & Reza Pourtaheri, 2024. "The Mt/M/1 queueing system with impatient customers and multiple vacation," OPSEARCH, Springer;Operational Research Society of India, vol. 61(4), pages 2002-2022, December.
    12. Tasos Nikoleris & Mark Hansen, 2012. "Queueing Models for Trajectory-Based Aircraft Operations," Transportation Science, INFORMS, vol. 46(4), pages 501-511, November.
    13. Adrian Otoiu & Emilia Titan, 2014. "An Alternative Method of Component Aggregation for Computing Multidimensional Well-Being Indicators," International Journal of Economic Sciences, Prague University of Economics and Business, vol. 2014(4), pages 38-52.
    14. Wang, Wenjun & Liu, Dong & Liu, Xiao & Pan, Lin, 2013. "Fuzzy overlapping community detection based on local random walk and multidimensional scaling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(24), pages 6578-6586.
    15. Yi-Chen Chung & Hsien-Ming Chou & Chih-Neng Hung & Chihli Hung, 2021. "Using Textual and Economic Features to Predict the RMB Exchange Rate," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 11(6), pages 1-8.
    16. Daniel, Joseph I. & Pahwa, Munish, 2000. "Comparison of Three Empirical Models of Airport Congestion Pricing," Journal of Urban Economics, Elsevier, vol. 47(1), pages 1-38, January.
    17. Chen-Yang Cheng, 2014. "Indoor localization algorithm using clustering on signal and coordination pattern," Annals of Operations Research, Springer, vol. 216(1), pages 83-99, May.
    18. Christmann, Andreas & Steinwart, Ingo & Hubert, Mia, 2006. "Robust Learning from Bites for Data Mining," Technical Reports 2006,03, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    19. Steven Buigut, 2015. "The Effect of Zimbabwe's Multi-Currency Arrangement on Bilateral Trade: Myth Versus Reality," International Journal of Economics and Financial Issues, Econjournals, vol. 5(3), pages 690-700.
    20. Defraeye, Mieke & Van Nieuwenhuyse, Inneke, 2016. "Staffing and scheduling under nonstationary demand for service: A literature review," Omega, Elsevier, vol. 58(C), pages 4-25.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ortrsc:v:50:y:2016:i:1:p:94-109. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.