A Scenario-Based Approach for the Air Traffic Flow Management Problem with Stochastic Capacities
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A Scenario-Based Approach for the Air Traffic Flow Management Problem with Stochastic Capacities

Authors: Soumia Ichoua


In this paper, we investigate the strategic stochastic air traffic flow management problem which seeks to balance airspace capacity and demand under weather disruptions. The goal is to reduce the need for myopic tactical decisions that do not account for probabilistic knowledge about the NAS near-future states. We present and discuss a scenario-based modeling approach based on a time-space stochastic process to depict weather disruption occurrences in the NAS. A solution framework is also proposed along with a distributed implementation aimed at overcoming scalability problems. Issues related to this implementation are also discussed.

Keywords: Air traffic management, sample average approximation, scenario-based approach, stochastic capacity.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1086509

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[1] Joint Economic Committee (JEC) (2008). Your flight has been delayed again: flight delays cost passengers, airlines, and the US economy billions. Available at: http://jec.senate.gov/index.cfm?FuseAction=Reports.Reports&ContentR ecord_id=11116dd7-973c-61e2-4874a6a18790a81b &Region_id=&Issue_id, accessed on Feb. 22, 2013.
[2] NextGen-Airspace. Available at: http://www.hq.nasa.gov/office/aero/asp/airspace/index.htm, accessed on Feb. 22, 2013.
[3] Ball, M. O., C. Barnhart, G. Nemhauser, A. Odoni. 2007. Air transportation: Irregular operations and control. C. Barnhart, G. Laporte, eds.Transportation. Handbooks in Operations Research and Management Science, Vol. 14. Elsevier, Amsterdam, 1–73.
[4] Hoffman, R., A. Mukherjee, T. Vossen. 2011. Air traffic flow management. C. Barnhart, B. Smith, eds. Quantitative Problem Solving Methods in the Airline Industry: A Modeling Methodology Handbook. International Series in Operations Research and Management Science. Springer, Norwell, MA.
[5] Lulli, G., Odoni, A.R.: The European Air Traffic Flow Management Problem. Transportation Science 41, 1–13 (2007)
[6] A. Nilim A. and L. El Ghaoui, L, “Algorithms for Air Traffic Flow Management under Stochastic Environments”, in Proc. American Control Conference, 2004, vol. 4, pp. 3429 – 3434.
[7] G. Clare and A. Richards, “Air traffic flow management under uncertainty: application of chance constraints”, in Proc. the 2nd International Conference on Application and Theory of Automation in Command and Control Systems, 2012, pp. 20-26.
[8] A. Agustın, A. Alonso-Ayuso , L.F. Escudero and C. Pizarro, “On air traffic flow management with rerouting. Part II: Stochastic case”, European Journal of Operational Research, vol. 219, pp. 167-177, 2012.
[9] G. Clare, A. Richards, J. Escartin, David Martınez, J. Cegarra and L. J. Alvarez, “Air Traffic Flow Management Under Uncertainty: Interactions Between Network Manager and Airline Operations Centre”, in Proc. second SESAR Innovation Days, 2012.
[10] C.N. Glover, “Computationally tractable stochastic integer programming models for air traffic flow management”, Doctoral dissertation, University of Maryland, College Park, 2010.
[11] A. Mukherjee and Mark Hansen, Dynamic Stochastic Optimization Model for Air Traffic Flow Management with En Route and Airport Capacity Constraints”, In Proc. the 6th USA/Europe Air Traffic Management Research and Development Seminar, which took place in Baltimore, Maryland, US, 2005.
[12] J.B. Marron, “The stochastic air traffic flow management rerouting problem”, M. Eng. Thesis, Massachusetts Institute of Technology, 2004.
[13] Y. Chang, “Stochastic programming approaches to air traffic flow management under the uncertainty of weather”, Doctoral dissertation, Georgia Institute of Technology, Atlanta. 2010.
[14] R. DeLaura and S. Allan, “Route selection decision support in convective weather: A case study of the effects of weather and operational assumptions on departure throughput,” USA/Europe Air Traffic Management R&D Seminar, Budapest, Hungary, June 2003.
[15] B.D. Martin and J. Evans, “Results of an exploratory study to model route availability in enroute airspace as a function of actual weather coverage and type,” Technical Report, MIT Lincoln Laboratory, 2005.
[16] B.D. Martin, J. Evans, and R. DeLaura, “Exploration of a model relating route availability in enroute airspace to actual weather coverage parameters,” 12th Conference on Aviation Range and Aerospace Meteorology, Atlanta, GA, January 2006.
[17] J.P. Clarke, Solak, S., Ren L. and Vela A.E., Determining Stochastic Airspace Capacity for Air Traffic Flow Management, Transportation Science, Articles in Advance, pp. 1–18, 2012.
[18] Steiner M, Krozel J (2009), “Translation of ensemble-based weather forecasts into probabilistic air traffic capacity impact”, n Proc. 28th Digital Avionics Systems Conf., October 25–29, Orlando, FL.
[19] S. Roy, Y. Wan, C. Taylor, and C. R. Wanke, “A Stochastic Network Model for Uncertain Spatiotemporal Weather Impact at the Strategic Time Horizon,” in AIAA Aviation Technology, Integration, and Operations Conference, no. September, 2010.
[20] M. Xue, S. Roy, S. Zobell, Y. Wan, C. Taylor, and C. Wanke, “A Stochastic Spatiotemporal Weather-Impact Simulator: Representative Scenario Selection,” in AIAA Aviation Technology, Integration, and Operations Conference, no. September, 2011.
[21] Ichoua, S., “Humanitarian Logistics Network Design for an Effective Disaster Response”, in the Proceedings of the 7th International Conference on Information Systems for Crisis Response and Management (ISCRAM), Seattle, Washington, pp. 14-17, 2010.
[22] Klibi , W., S. Ichoua and A. Martel, “Designing Emergency Supply Networks for Responsive Disaster Support”, in the Proceedings of the Fifth International Workshop on Freight Transportation and Logistics (ODYSSEUS 2012), Mykonos Island, Greece, pp. 505-508, 2012.
[23] Bertsimas D., Lulli G., Odoni A.R., “An Integer Optimization Approach to Large-Scale Air Traffic Flow Management”, Operations Research, Vol. 59(1), pp. 211–227, 2011.