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Modeling Crew Itineraries and Delays in the National Air Transportation System

Author

Listed:
  • Keji Wei

    (Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire 03755)

  • Vikrant Vaze

    (Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire 03755)

Abstract

We propose, optimize, and validate a methodological framework for estimating the extent of the crew-propagated delays and disruptions (CPDDs). We identify the factors that influence the extent of the CPDDs and incorporate them into a robust crew-scheduling model. We develop a fast heuristic approach for solving the inverse of this robust crew-scheduling problem to generate crew schedules that are similar to real-world crew-scheduling samples. We develop a sequence of exact and heuristic techniques to quickly solve the forward problem within a small optimality gap for network sizes that are among the largest in robust crew-scheduling literature. Computational results using four large real-world airline networks demonstrate that the crew schedules produced by our approach generate propagation patterns similar to those observed in the real world. Extensive out-of-sample validation tests indicate that the parameters calibrated for one network perform reasonably well for other networks. We provide new insights into the perceived trade-off between planned costs and delay costs as reflected by actual airline crew schedules. Finally, we present a general approach to estimate the CPDDs for any given network using our methodological framework under a variety of data availability scenarios.

Suggested Citation

  • Keji Wei & Vikrant Vaze, 2018. "Modeling Crew Itineraries and Delays in the National Air Transportation System," Transportation Science, INFORMS, vol. 52(5), pages 1276-1296, October.
  • Handle: RePEc:inm:ortrsc:v:52:y:2018:i:5:p:1276-1296
    DOI: 10.1287/trsc.2018.0834
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    References listed on IDEAS

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    3. Li, Max Z. & Ryerson, Megan S., 2019. "Reviewing the DATAS of aviation research data: Diversity, availability, tractability, applicability, and sources," Journal of Air Transport Management, Elsevier, vol. 75(C), pages 111-130.
    4. Zhou, Yaoming & Wang, Junwei & Huang, George Q., 2019. "Efficiency and robustness of weighted air transport networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 14-26.
    5. Wen, Xin & Chung, Sai-Ho & Ji, Ping & Sheu, Jiuh-Biing, 2022. "Individual scheduling approach for multi-class airline cabin crew with manpower requirement heterogeneity," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 163(C).
    6. Choi, Tsan-Ming & Wen, Xin & Sun, Xuting & Chung, Sai-Ho, 2019. "The mean-variance approach for global supply chain risk analysis with air logistics in the blockchain technology era," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 127(C), pages 178-191.
    7. Alexandre Jacquillat & Vikrant Vaze, 2018. "Interairline Equity in Airport Scheduling Interventions," Transportation Science, INFORMS, vol. 52(4), pages 941-964, August.

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