A dynamic integer programming approach for free flight air traffic management (ATM) scenario with 4D-trajectories and energy efficiency aspects

Abstract

The growth in demand for air transport has generated new challenges for capacity and safety. In response, manufacturers develop new types of aircraft while airlines open new routes and adapt their fleet. This excessive demand for air transport also leads to the need for further investments in airport expansion and ATM modernization. The current work was focused on the ATM problem with respect to new procedures, such as free flight, for addressing the air capacity issues in an environmental approach. The study was triggered by and aligned with the following performance objectives set by EUROCONTROL and the European Commission: (1) to improve ATM safety whilst accommodating air traffic growth; (2) to increase the ATM network efficiency; (3) to strengthen ATM’s contribution to aviation security and to environmental objectives; (4) to match capacity and air transport growth. The proposed mathematical model covers the aforementioned objectives by focusing on energy losses and costs of flights under the scenario of a controlled free flight and a unified airspace. The factors enhanced in the model were chosen based on their impact on the ATM energy efficiency, such as the airborne delays and flight duration, the delays due to ground holding, the flight cancellation, the flight speed deviations and the flight level alterations. Therefore, the presented mathematical model minimizes the energy costs due to the above terms under certain assumptions and constraints. Finally, simulation case studies, used as proof tests, have been conducted under different ATM scenarios to examine the complexity and the efficiency of the developed model.

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References

  1. 1.

    Air Transport Action Group (ATAG): Benefits Beyond Borders. ATAG, Geneva (2018)

    Google Scholar 

  2. 2.

    PwC, A4E: The Economic Impact of ATC: Strikes in Europe. PwC, London (2016)

    Google Scholar 

  3. 3.

    CODA DIGEST: All-causes delay and cancellations to air transport in Europe. EUROCONTROL (2018)

  4. 4.

    Billette de Villemeur, E., Ivaldi, M., Quinet, E., Urdanoz, M.: The social cost of air traffic delays (Dec 2014)

  5. 5.

    ATAG - Air Transport Action Group: Revolutionising air traffic management—practical steps to accelerating airspace efficiency in your region (2012)

  6. 6.

    IATA: Economic benefits of European airspace modernization. SEO Amsterdam Economics, Amsterdam (2016)

    Google Scholar 

  7. 7.

    Airports Commission: Airports commission: interim report (Dec 2013)

  8. 8.

    Airports Commission: Economy: delay impacts assessment (Nov 2015)

  9. 9.

    Prospect, ETF and ATCEUC: Efficiency, capacity and growth in European aviation: why industrial action in ATM is not the issue. PricewaterhouseCoopers LLP (PwC) (2016)

  10. 10.

    Sternberg, A., Soares, J., Carvalho, D., Ogasawara, E.: A review on flight delay prediction. In: CEFET/RJ (2017)

  11. 11.

    Le Quéré, C., Andrew, R.M., Friedlingstein, P., Sitch, S., Hauck, J., Pongratz, J., Pickers, P.A., Korsbakken, J.I., Peters, G.P., Canadell, J.G., Arneth, A., Arora, V.K., Barbero, L., Bastos, A., Bopp, L., Chevallier, F., Chini, L.P., Ciais, P., Doney, S.C., Gkritzalis, T., Goll, D.S., Harris, I., Haverd, V., Hoffman, F.M., Hoppema, M., Houghton, R.A., Hurtt, G., Ilyina, T., Jain, A.K., Johannessen, T., Jones, C.D., Kato, E., Keeling, R.F., Goldewijk, K.K., Landschützer, P., Lefèvre, N., Lienert, S., Liu, Z., Lombardozzi, D., Metzl, N., Munro, D.R.: Global Carbon Budget 2018. Earth Syst. Sci. Data 10, 2141–2194 (2018)

    Article  Google Scholar 

  12. 12.

    Figuere, C., Le Quéré, C., Mahindra, A., Bäte, O., Whiteman, G., Peters, G., Guan, D.: Emissions are still rising: ramp up the cuts. Nature 564, 27–30 (2018)

    Article  Google Scholar 

  13. 13.

    Kousoulidou, M., Lonza, L.: Biofuels in aviation: fuel demand and CO2 emissions evolution in Europe toward 2030. Transp. Res. Part D Transp. Environ. 46, 166–181 (2016)

    Article  Google Scholar 

  14. 14.

    Bianco, L., Rinaldi, G., Sassano, A.: A combinatorial optimization approach to aircraft sequencing problem. In: Odoni, A.R., Bianco, L., Szego, G. (eds.) Flow Control of Congested Networks, pp. 323–339. Springer, Berlin (1987)

    Google Scholar 

  15. 15.

    Bianco, L.: Trends in transportation system and relation with air transportation demand. In: Advanced Workshop in Air Traffic Control, Capri, Italy (1995)

  16. 16.

    Andreatta, G., Romain-Jacur, G.: Aircraft flow management under congestion. Transp. Sci. 21(4), 227–292 (1987)

    Article  Google Scholar 

  17. 17.

    Andreatta, G., Odoni, A.R., Richetta, O.: Models for the ground holding problem. In: Odoni, L.B.A.A. (ed.) Large Scale Computation and Information Processing in Air Traffic Control, pp. 125–168. Springer, Berlin (1993)

    Google Scholar 

  18. 18.

    Richetta, O.: Optimal algorithms and a remarkably efficient heuristic for the ground holding problem in air traffic control. Oper. Res. 43(5), 728–905 (1995)

    Article  Google Scholar 

  19. 19.

    Platz, K., Brokof, U.: Optimising air traffic flow at airports. In: Winter, H., Nüßer, H.G. (eds.) Advanced Technologies for Air Traffic Flow Management. Lecture Notes in Control and Information Sciences, vol. 198. Springer, Berlin, Heidelberg (1994)

    Google Scholar 

  20. 20.

    Wang, A.: Dynamic programming framework for the global flow control problem in air traffic management. Transp. Sci. 4(25), 308–313 (1991)

    Article  Google Scholar 

  21. 21.

    Gilbo, E.G.: Airport capacity: representation, estimation and optimization. IEEE Trans. Control Syst. Technol. 3(1), 144–154 (1993)

    Article  Google Scholar 

  22. 22.

    Andreatta, G., Brunetta, L.: Multi-airport ground holding problem: a computational evaluation of exact algorithms. Oper. Res. 1(46), 57–64 (1998)

    Article  Google Scholar 

  23. 23.

    Andreatta, G., Brunetta, L., Guastalla, G.: Multi-airport ground holding problem: A heuristic approach based on priority rules. In: Bianco, L., Dell’Olmo, P., Odoni, A.R. (eds.) Modelling and Simulation in Air Traffic Management, pp. 71–89. Springer, Berlin (1997)

    Google Scholar 

  24. 24.

    Bertsimas, D., Stock, S.: The multi airport flow management problem with en route capacities. Oper. Res. 46(3), 406–422 (1998)

    Article  Google Scholar 

  25. 25.

    Dell’Olmo, P., Lulli, G.: The European air traffic flow management problem. In: IFAC Proceedings Volumes, vol. 39, no. 12, pp. 96–100 (2006)

  26. 26.

    Krozel, J., Jakobovits, R., Penny, S.: An algorithmic approach for airspace flow programs. Air Traffic Control Q. 14(3), 203–229 (2006)

    Article  Google Scholar 

  27. 27.

    Koepke, C.G., Armacost, A.P., Barnhart, C., Kolitz, S.E.: An integer programming approach to support the US Air Force’s air mobility network. Comput. Oper. Res. 35(6), 1771–1788 (2008)

    Article  Google Scholar 

  28. 28.

    Bertsimas, D., Stock, S.: The traffic flow management rerouting problem in air traffic control: a dynamic network flow approach. Transp. Sci. 34(3), 239–255 (2000)

    Article  Google Scholar 

  29. 29.

    Leal de Matos, P., Chen, B., Ormerod, R.: Optimization models for re-routing air traffic flows. J. Oper. Res. Soc. 52(12), 1338–1349 (2001)

    Article  Google Scholar 

  30. 30.

    Richards, A., How, J.P.: Aircraft trajectory planning with collision avoidance using mixed integer linear programming. In: American Control Conference (IEEE Cat. No.CH37301), Anchorage, AK, USA (2002)

  31. 31.

    Betsimas, D., Lulli, G., Odoni, A.: The air traffic flow management problem: an integer optimization approach. In: 13th International Conference of Integer Programming and Combinatorial Optimization, Bertinoro, Italy (2008)

  32. 32.

    Alonso-Ayuso, A., Escudero, L.F.: A stochastic 0–1 program based approach for air traffic management. Eur. J. Oper. Res. 120(1), 47–62 (2000)

    Article  Google Scholar 

  33. 33.

    Grignon, L.: Analyses of Delay in an Air Traffic System with Weather Uncertainty. University of Washington, Washington, DC (2002)

    Google Scholar 

  34. 34.

    D’aspremont, A., Sohier, D., Nilim, A., El Ghaoui, L., Duong, V.: Optimal path planning for air traffic flow management under stochastic weather and capacity constraints. In: 2006 International Conference on Research, Innovation and Vision for the Future. IEEE (2006)

  35. 35.

    Goni-Modrego, E., Iagaru, M.G., Dalichampt, M., Lane, R.: Airport CDM network impact assessment. In: Eighth USA/Europe Air Traffic Management Research and Development Seminar, Napa (California, USA) (2009)

  36. 36.

    Delahaye, D., Puechmorel, S., Tsiotras, P., Feron, E.: Mathematical models for aircraft trajectory design: a survey. Lect. Notes Electr. Eng. 5(290), 205–247 (2014)

    Article  Google Scholar 

  37. 37.

    Blom, H.A., Bakker, G.J., Klein Obbink, B.. Klompstra, M. B.: Free flight safety risk modelling and simulation. In: 2nd International Conference on Research in Air Transportation ICRAT 2006, at Beograd, Serbia, June 24–28, 2006

  38. 38.

    Moeini, G.: En-route flight planning: a mathematical modeling approach for operating cost minimization, dynamic speed control and mid-air collision avoidance. A Thesis, Concordia University, Montreal, Quebec, Canada (2013)

  39. 39.

    Torres, S., Delpome, K.L.: An integrated approach to air traffic management to achieve trajectory based operations. In: 2012 IEEE/AIAA 31st Digital Avionics Systems Conference (DASC), Williamsburg, VA, USA (2012)

  40. 40.

    Huang, Y., Rebennack, S., Zheng, Q.P.: Techno-economic analysis and optimization models for carbon capture and storage: a survey. Energy Syst. 4(4), 315–353 (2013)

    Article  Google Scholar 

  41. 41.

    Ibanez, E., McCalley, J.D.: Multiobjective evolutionary algorithm for long-term planning of the national energy and transportation systems. Energy Syst. 2(2), 151–169 (2011)

    Article  Google Scholar 

  42. 42.

    Ntakolia, C., Coletsos, J.: Air traffic management and energy efficiency: the free flight concept. Energy Syst. (ENSY) 8(4), 709–726 (2017)

    Article  Google Scholar 

  43. 43.

    Aegean. http://el.about.aegeanair.com/etaireia/stolos/. Accessed 08 June 2016

  44. 44.

    IBM. https://www.ibm.com/support/knowledgecenter/SS9UKU_12.5.0/com.ibm.cplex.zos.help/UsrMan/topics/discr_optim/mip/troubleshoot/61_mem_gone.html. Accessed 30 May 2017

  45. 45.

    Carle, M.-A.: The quest for optimality. http://www.thequestforoptimality.com/closing-the-gap-part-i/#comments. Accessed 28 May 2017

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Acknowledgements

We thank the Papakyriakopoulos Institution for granting Dr. Charis Ntakolia and supporting her Ph.D. work from June 2015 to June 2017.

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Correspondence to Charis Ntakolia.

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The original version of the article was revised. First and surname tagging of all authors in author group were corrected.

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Ntakolia, C., Caceres, H. & Coletsos, J. A dynamic integer programming approach for free flight air traffic management (ATM) scenario with 4D-trajectories and energy efficiency aspects. Optim Lett 14, 1659–1680 (2020). https://doi.org/10.1007/s11590-019-01458-1

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Keywords

  • Operations research
  • Integer linear programming
  • Dynamic programming
  • Air traffic management
  • Energy efficiency