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Improving aircraft approach operations taking into account noise and fuel consumption

Author

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  • Rodríguez-Díaz, A.
  • Adenso-Díaz, B.
  • González-Torre, P.L.

Abstract

While air transport brings very significant economic and social benefits to the cities and regions served by airports, aircraft noise is the single major cause of community opposition to airport operations, becoming a critical issue that affects the sustainability of future traffic growth. However, planning operations exclusively focusing on noise impact may result in an increase of fuel consumption or delays. This paper develops a suitable bi-objective model for landing aircraft, which finds a schedule that minimises noise impact, total fuel consumption and delays, under wake vortex separation and Constrained Position Shifting restrictions. The results of this model are compared with real operations in a major European airport to assess the potential level of improvements. By comparing with real data from Madrid-Barajas airport, the research shows potential improvements of up to 4.5% reduction of total fuel consumption (without increasing noise levels) only by modifying the sequence of arrivals, and up to 43% (without extra fuel consumption) of reduction in noise impact over the populations under study.

Suggested Citation

  • Rodríguez-Díaz, A. & Adenso-Díaz, B. & González-Torre, P.L., 2019. "Improving aircraft approach operations taking into account noise and fuel consumption," Journal of Air Transport Management, Elsevier, vol. 77(C), pages 46-56.
  • Handle: RePEc:eee:jaitra:v:77:y:2019:i:c:p:46-56
    DOI: 10.1016/j.jairtraman.2019.03.004
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    References listed on IDEAS

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    1. Julia Bennell & Mohammad Mesgarpour & Chris Potts, 2013. "Airport runway scheduling," Annals of Operations Research, Springer, vol. 204(1), pages 249-270, April.
    2. Laumanns, Marco & Thiele, Lothar & Zitzler, Eckart, 2006. "An efficient, adaptive parameter variation scheme for metaheuristics based on the epsilon-constraint method," European Journal of Operational Research, Elsevier, vol. 169(3), pages 932-942, March.
    3. Torija, Antonio J. & Self, Rod H., 2018. "Aircraft classification for efficient modelling of environmental noise impact of aviation," Journal of Air Transport Management, Elsevier, vol. 67(C), pages 157-168.
    4. Postorino, Maria Nadia & Mantecchini, Luca, 2016. "A systematic approach to assess the effectiveness of airport noise mitigation strategies," Journal of Air Transport Management, Elsevier, vol. 50(C), pages 71-82.
    5. Andreas W. Schäfer & Steven R. H. Barrett & Khan Doyme & Lynnette M. Dray & Albert R. Gnadt & Rod Self & Aidan O’Sullivan & Athanasios P. Synodinos & Antonio J. Torija, 2019. "Technological, economic and environmental prospects of all-electric aircraft," Nature Energy, Nature, vol. 4(2), pages 160-166, February.
    6. Artiouchine, Konstantin & Baptiste, Philippe & Dürr, Christoph, 2008. "Runway sequencing with holding patterns," European Journal of Operational Research, Elsevier, vol. 189(3), pages 1254-1266, September.
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