IDEAS home Printed from https://ideas.repec.org/a/eee/transb/v43y2009i1p159-171.html
   My bibliography  Save this article

A dynamic rerouting model for air traffic flow management

Author

Listed:
  • Mukherjee, Avijit
  • Hansen, Mark

Abstract

In this paper, we present a stochastic integer programming model for managing air traffic inbound to an airport when both the airport itself and its approach routes are subject to adverse weather. In the model, ground delay decisions are static, while those on rerouting are dynamic. The decision variables in the model are aggregate number of flights planned to arrive at various capacity constrained resources. The model does not directly assign arrival times to individual flights. Therefore, in context of Collaborative Decision Making, which is the governing philosophy of the air traffic management system of the United States, the solutions from the dynamic rerouting model can be directly fed to some resource allocation algorithm that assigns routes and release times to individual flights or to the airlines who operate them. When adverse weather blocks or severely limits capacity of terminal approach routes, rerouting flights onto other approaches yields substantial benefits by alleviating high ground delays. Our experimental results indicate that making rerouting decisions dynamically results in 10-15% delay cost reduction compared to static rerouting, and about 50% less delay cost compared to a "pure" ground holding strategy (i.e., no rerouting). In contrast to static rerouting, the dynamic rerouting capability results in making rerouting decisions that are better matched to realized weather conditions. Lower total expected delay cost is achieved by delaying the rerouting decisions for flights until they reach the divergence point between alternative routes, and hence exploiting updated information on weather while making those decisions. In cases where the airport is the main, but not the only, bottleneck, the dynamic rerouting model may assign higher ground delays so that the rerouting decisions can be deferred until more information on en route weather becomes available.

Suggested Citation

  • Mukherjee, Avijit & Hansen, Mark, 2009. "A dynamic rerouting model for air traffic flow management," Transportation Research Part B: Methodological, Elsevier, vol. 43(1), pages 159-171, January.
  • Handle: RePEc:eee:transb:v:43:y:2009:i:1:p:159-171
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0191-2615(08)00067-2
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Avijit Mukherjee & Mark Hansen, 2007. "A Dynamic Stochastic Model for the Single Airport Ground Holding Problem," Transportation Science, INFORMS, vol. 41(4), pages 444-456, November.
    2. Mukherjee, Avijit, 2004. "Dynamic Stochastic Optimization Models for Air Traffic Flow Management," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt2vk8w6nc, Institute of Transportation Studies, UC Berkeley.
    3. Thomas W. M. Vossen & Michael O. Ball, 2006. "Slot Trading Opportunities in Collaborative Ground Delay Programs," Transportation Science, INFORMS, vol. 40(1), pages 29-43, February.
    4. Octavio Richetta & Amedeo R. Odoni, 1993. "Solving Optimally the Static Ground-Holding Policy Problem in Air Traffic Control," Transportation Science, INFORMS, vol. 27(3), pages 228-238, August.
    5. Michael O. Ball & Robert Hoffman & Amedeo R. Odoni & Ryan Rifkin, 2003. "A Stochastic Integer Program with Dual Network Structure and Its Application to the Ground-Holding Problem," Operations Research, INFORMS, vol. 51(1), pages 167-171, February.
    6. 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.
    7. Gulpinar, Nalan & Rustem, Berc & Settergren, Reuben, 2004. "Simulation and optimization approaches to scenario tree generation," Journal of Economic Dynamics and Control, Elsevier, vol. 28(7), pages 1291-1315, April.
    8. Balázs Kotnyek & Octavio Richetta, 2006. "Equitable Models for the Stochastic Ground-Holding Problem Under Collaborative Decision Making," Transportation Science, INFORMS, vol. 40(2), pages 133-146, May.
    9. Richetta, Octavio & Odoni, Amedeo R., 1994. "Dynamic solution to the ground-holding problem in air traffic control," Transportation Research Part A: Policy and Practice, Elsevier, vol. 28(3), pages 167-185, May.
    10. Dimitris Bertsimas & Sarah Stock Patterson, 2000. "The Traffic Flow Management Rerouting Problem in Air Traffic Control: A Dynamic Network Flow Approach," Transportation Science, INFORMS, vol. 34(3), pages 239-255, August.
    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. Wesonga, Ronald, 2015. "Airport utility stochastic optimization models for air traffic flow management," European Journal of Operational Research, Elsevier, vol. 242(3), pages 999-1007.
    2. Linlin Chen & Shuihua Han & Chaokan Du & Zongwei Luo, 2022. "A real-time integrated optimization of the aircraft holding time and rerouting under risk area," Annals of Operations Research, Springer, vol. 310(1), pages 7-26, March.
    3. Murça, Mayara Condé Rocha, 2018. "Collaborative air traffic flow management: Incorporating airline preferences in rerouting decisions," Journal of Air Transport Management, Elsevier, vol. 71(C), pages 97-107.
    4. Zhang, Qiuhan & Le, Meilong & Xu, Yan, 2021. "Collaborative delay management towards demand-capacity balancing within User Driven Prioritisation Process," Journal of Air Transport Management, Elsevier, vol. 91(C).
    5. Yong Tian & Bojia Ye & Marc Sáez Estupiñá & Lili Wan, 2018. "Stochastic Simulation Optimization for Route Selection Strategy Based on Flight Delay Cost," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 35(06), pages 1-24, December.
    6. 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.
    7. Chen, Dan & Hu, Minghua & Zhang, Honghai & Yin, Jianan & Han, Ke, 2017. "A network based dynamic air traffic flow model for en route airspace system traffic flow optimization," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 106(C), pages 1-19.
    8. Künnen, Jan-Rasmus & Strauss, Arne K., 2022. "The value of flexible flight-to-route assignments in pre-tactical air traffic management," Transportation Research Part B: Methodological, Elsevier, vol. 160(C), pages 76-96.
    9. Xu, Yan & Dalmau, Ramon & Melgosa, Marc & Montlaur, Adeline & Prats, Xavier, 2020. "A framework for collaborative air traffic flow management minimizing costs for airspace users: Enabling trajectory options and flexible pre-tactical delay management," Transportation Research Part B: Methodological, Elsevier, vol. 134(C), pages 229-255.
    10. Chen, J. & Chen, L. & Sun, D., 2017. "Air traffic flow management under uncertainty using chance-constrained optimization," Transportation Research Part B: Methodological, Elsevier, vol. 102(C), pages 124-141.
    11. John-Paul B. Clarke & Senay Solak & Liling Ren & Adan E. Vela, 2013. "Determining Stochastic Airspace Capacity for Air Traffic Flow Management," Transportation Science, INFORMS, vol. 47(4), pages 542-559, November.
    12. Diao, Xudong & Chen, Chun-Hsien, 2018. "A sequence model for air traffic flow management rerouting problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 110(C), pages 15-30.
    13. Shen, Ching-Cheng & Yeh, Chien-Chi & Lin, Chun-Nan, 2022. "Using the perspective of business information technology technicians to explore how information technology affects business competitive advantage," Technological Forecasting and Social Change, Elsevier, vol. 184(C).

    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. Dixit, Aasheesh & Jakhar, Suresh Kumar, 2021. "Airport capacity management: A review and bibliometric analysis," Journal of Air Transport Management, Elsevier, vol. 91(C).
    2. Michael O. Ball & Robert Hoffman & Avijit Mukherjee, 2010. "Ground Delay Program Planning Under Uncertainty Based on the Ration-by-Distance Principle," Transportation Science, INFORMS, vol. 44(1), pages 1-14, February.
    3. Alexander S. Estes & Michael O. Ball, 2020. "Equity and Strength in Stochastic Integer Programming Models for the Dynamic Single Airport Ground-Holding Problem," Transportation Science, INFORMS, vol. 54(4), pages 944-955, July.
    4. 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.
    5. Murça, Mayara Condé Rocha, 2018. "Collaborative air traffic flow management: Incorporating airline preferences in rerouting decisions," Journal of Air Transport Management, Elsevier, vol. 71(C), pages 97-107.
    6. Yi Liu & Mark Hansen, 2016. "Incorporating Predictability Into Cost Optimization for Ground Delay Programs," Transportation Science, INFORMS, vol. 50(1), pages 132-149, February.
    7. Avijit Mukherjee & Mark Hansen & Shon Grabbe, 2012. "Ground delay program planning under uncertainty in airport capacity," Transportation Planning and Technology, Taylor & Francis Journals, vol. 35(6), pages 611-628, June.
    8. Chen, J. & Chen, L. & Sun, D., 2017. "Air traffic flow management under uncertainty using chance-constrained optimization," Transportation Research Part B: Methodological, Elsevier, vol. 102(C), pages 124-141.
    9. Avijit Mukherjee & Mark Hansen, 2007. "A Dynamic Stochastic Model for the Single Airport Ground Holding Problem," Transportation Science, INFORMS, vol. 41(4), pages 444-456, November.
    10. Mukherjee, Avijit, 2004. "Dynamic Stochastic Optimization Models for Air Traffic Flow Management," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt2vk8w6nc, Institute of Transportation Studies, UC Berkeley.
    11. Guglielmo Lulli & Amedeo Odoni, 2007. "The European Air Traffic Flow Management Problem," Transportation Science, INFORMS, vol. 41(4), pages 431-443, November.
    12. Alexander S. Estes & Michael O. Ball, 2021. "Monge Properties, Optimal Greedy Policies, and Policy Improvement for the Dynamic Stochastic Transportation Problem," INFORMS Journal on Computing, INFORMS, vol. 33(2), pages 785-807, May.
    13. Cynthia Barnhart & Dimitris Bertsimas & Constantine Caramanis & Douglas Fearing, 2012. "Equitable and Efficient Coordination in Traffic Flow Management," Transportation Science, INFORMS, vol. 46(2), pages 262-280, May.
    14. Woo, Young-Bin & Moon, Ilkyeong, 2021. "Scenario-based stochastic programming for an airline-driven flight rescheduling problem under ground delay programs," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 150(C).
    15. Balázs Kotnyek & Octavio Richetta, 2006. "Equitable Models for the Stochastic Ground-Holding Problem Under Collaborative Decision Making," Transportation Science, INFORMS, vol. 40(2), pages 133-146, May.
    16. Brunner, Jens O., 2014. "Rescheduling of flights during ground delay programs with consideration of passenger and crew connections," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 72(C), pages 236-252.
    17. Xu, Yan & Dalmau, Ramon & Melgosa, Marc & Montlaur, Adeline & Prats, Xavier, 2020. "A framework for collaborative air traffic flow management minimizing costs for airspace users: Enabling trajectory options and flexible pre-tactical delay management," Transportation Research Part B: Methodological, Elsevier, vol. 134(C), pages 229-255.
    18. Guo, Yechenfeng & Hu, Minghua & Zou, Bo & Hansen, Mark & Zhang, Ying & Xie, Hua, 2022. "Air Traffic Flow Management Integrating Separation Management and Ground Holding: An Efficiency-Equity Bi-objective Perspective," Transportation Research Part B: Methodological, Elsevier, vol. 155(C), pages 394-423.
    19. Xiangning Dong & Xuhao Zhu & Minghua Hu & Jie Bao, 2023. "A Methodology for Predicting Ground Delay Program Incidence through Machine Learning," Sustainability, MDPI, vol. 15(8), pages 1-19, April.
    20. Andreatta, Giovanni & Dell'Olmo, Paolo & Lulli, Guglielmo, 2011. "An aggregate stochastic programming model for air traffic flow management," European Journal of Operational Research, Elsevier, vol. 215(3), pages 697-704, December.

    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:eee:transb:v:43:y:2009:i:1:p:159-171. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/548/description#description .

    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.