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Improving Airline Network Robustness and Operational Reliability by Sequential Optimisation Algorithms

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  • Cheng-Lung Wu

Abstract

A sequential optimisation algorithm is developed to improve the operational reliability of airline schedules. Simulation results show that departure delays are reduced by 30% after optimisation by using extra 260 min buffer times in the schedule. This also increases the network-wide schedule reliability from 37 to 52% and an estimated delay cost saving of $20 million dollars per annum for a small airline network. The advantage of sequential optimisation is that it considers the delay/punctuality propagation in airline networks, so to prevent airlines from planning excessive buffer times to individual flights by considering aircraft rotation as a whole process. Copyright Springer Science + Business Media, LLC 2006

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  • Cheng-Lung Wu, 2006. "Improving Airline Network Robustness and Operational Reliability by Sequential Optimisation Algorithms," Networks and Spatial Economics, Springer, vol. 6(3), pages 235-251, September.
    • Handle: RePEc:kap:netspa:v:6:y:2006:i:3:p:235-251
    DOI: 10.1007/s11067-006-9282-y
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    References listed on IDEAS

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    Cited by:

    1. Bai, Bingfeng, 2022. "Strategic business management for airport alliance: A complex network approach to simulation robustness analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    2. Yimga, Jules & Gorjidooz, Javad, 2019. "Airline schedule padding and consumer choice behavior," Journal of Air Transport Management, Elsevier, vol. 78(C), pages 71-79.
    3. Wu, Cheng-Lung & Law, Kristie, 2019. "Modelling the delay propagation effects of multiple resource connections in an airline network using a Bayesian network model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 62-77.
    4. Michelle Dunbar & Gary Froyland & Cheng-Lung Wu, 2012. "Robust Airline Schedule Planning: Minimizing Propagated Delay in an Integrated Routing and Crewing Framework," Transportation Science, INFORMS, vol. 46(2), pages 204-216, May.
    5. Mazhar Arıkan & Vinayak Deshpande & Milind Sohoni, 2013. "Building Reliable Air-Travel Infrastructure Using Empirical Data and Stochastic Models of Airline Networks," Operations Research, INFORMS, vol. 61(1), pages 45-64, February.
    6. Schultz, Michael & Evler, Jan & Asadi, Ehsan & Preis, Henning & Fricke, Hartmut & Wu, Cheng-Lung, 2020. "Future aircraft turnaround operations considering post-pandemic requirements," Journal of Air Transport Management, Elsevier, vol. 89(C).
    7. Thi-Phuong Nguyen, 2022. "Evaluation of network reliability for stochastic-flow air transportation network considering discounted fares from airlines," Annals of Operations Research, Springer, vol. 311(1), pages 335-355, April.
    8. van Schilt, Isabelle M. & van Kalker, Jonna & Lefter, Iulia & Kwakkel, Jan H. & Verbraeck, Alexander, 2024. "Buffer scheduling for improving on-time performance and connectivity with a multi-objective simulation–optimization model: A proof of concept for the airline industry," Journal of Air Transport Management, Elsevier, vol. 115(C).

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