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An Optimization Model for Assessing Flight Technical Delay

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  • Jinn-Tsai Wong
  • Sui-Ling Li
  • David Gillingwater

Abstract

This paper identifies the causes as well as the practical measurement of aircraft flight delays. The performance of air traffic management is measured by examining technical delays and scheduled timetable delays, which are derived from a mathematical programming model. To validate the optimization model, flight delays are simulated under various service rules. The outcome of the simulation runs shows that the average delay for each aircraft estimated from the optimization model is marginally higher than that from the simulation run under the "first come first serve" rule. However, under the "arrival flight first" rule, the optimization model's results are either higher or lower than those of the simulation model. Nonetheless, both sets of simulated delays are strongly correlated with those of the optimization model. Results from regression analyses show that the optimization model has the capacity to predict flight technical delays.

Suggested Citation

  • Jinn-Tsai Wong & Sui-Ling Li & David Gillingwater, 2002. "An Optimization Model for Assessing Flight Technical Delay," Transportation Planning and Technology, Taylor & Francis Journals, vol. 25(2), pages 121-153, January.
    • Handle: RePEc:taf:transp:v:25:y:2002:i:2:p:121-153
    DOI: 10.1080/03081060290033212
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    Cited by:

    1. Abdel-Aty, Mohamed & Lee, Chris & Bai, Yuqiong & Li, Xin & Michalak, Martin, 2007. "Detecting periodic patterns of arrival delay," Journal of Air Transport Management, Elsevier, vol. 13(6), pages 355-361.
    2. Y. X. Lee & Z. W. Zhong, 2016. "A study of the relationship between adverse weather conditions and flight delay," Journal of Advances in Technology and Engineering Research, A/Professor Akbar A. Khatibi, vol. 2(4), pages 112-117.

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