IDEAS home Printed from https://ideas.repec.org/a/inm/orinte/v56y2026i1p58-75.html

Decision Support for Schedule Recovery at Lufthansa Group Airlines

Author

Listed:
  • Toby O. Davies

    (Google Research, Pyrmont, New South Wales 2009, Australia)

  • Daniel Duque

    (Google Research, Cambridge, Massachusetts 02142)

  • Emily Masten

    (Google Research, Cambridge, Massachusetts 02142)

  • Tom Tangl

    (Google Research, 75009 Paris, France)

  • Eric Bruneton

    (Google Research, 75009 Paris, France)

  • Alejandra Estanislao

    (Google Research, 8004 Zürich, Switzerland)

  • Jon Orwant

    (Google Research, Cambridge, Massachusetts 02142)

  • Daniel Bogado Duffner

    (Swiss International Airlines, 8302 Zürich, Switzerland)

  • Michael Frey

    (Swiss International Airlines, 8302 Zürich, Switzerland)

  • Christian Most

    (Lufthansa Airlines, 60546 Frankfurt, Germany)

Abstract

In 2019, Lufthansa and Google began a five-year collaboration to apply operations research techniques to operational airline schedule recovery, jointly optimizing over aircraft, passengers, and crew to ensure that disruptions such as flight delays are mitigated smoothly. The resulting Operations Decision Support Suite (OPSD) implements several novel decomposition techniques and heuristics. The service is in daily use by Lufthansa subsidiary Swiss International Airlines, with EUR 12 million and 14 kilotons of CO 2 already saved. It is currently being deployed to all airlines in the Lufthansa Group and is on track to save EUR 30 million and 50 kilotons of CO 2 annually.

Suggested Citation

  • Toby O. Davies & Daniel Duque & Emily Masten & Tom Tangl & Eric Bruneton & Alejandra Estanislao & Jon Orwant & Daniel Bogado Duffner & Michael Frey & Christian Most, 2026. "Decision Support for Schedule Recovery at Lufthansa Group Airlines," Interfaces, INFORMS, vol. 56(1), pages 58-75, January.
    • Handle: RePEc:inm:orinte:v:56:y:2026:i:1:p:58-75
    DOI: 10.1287/inte.2025.0296
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/inte.2025.0296
    Download Restriction: no
    File URL: https://libkey.io/10.1287/inte.2025.0296?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Christian Artigues & Eric Bourreau & H. Murat Afsar & Olivier Briant & Mourad Boudia, 2012. "Disruption management for commercial airlines: methods and results for the ROADEF 2009 Challenge," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 6(6), pages 669-689.
    2. Desaulniers, G. & Desrosiers, J. & Dumas, Y. & Marc, S. & Rioux, B. & Solomon, M. M. & Soumis, F., 1997. "Crew pairing at Air France," European Journal of Operational Research, Elsevier, vol. 97(2), pages 245-259, March.
    3. Parmentier, Axel & Meunier, Frédéric, 2020. "Aircraft routing and crew pairing: Updated algorithms at Air France," Omega, Elsevier, vol. 93(C).
    4. Uğur Arıkan & Sinan Gürel & M. Selim Aktürk, 2017. "Flight Network-Based Approach for Integrated Airline Recovery with Cruise Speed Control," Transportation Science, INFORMS, vol. 51(4), pages 1259-1287, November.
    5. Jon D. Petersen & Gustaf Sölveling & John-Paul Clarke & Ellis L. Johnson & Sergey Shebalov, 2012. "An Optimization Approach to Airline Integrated Recovery," Transportation Science, INFORMS, vol. 46(4), pages 482-500, November.
    6. Khaled, Oumaima & Minoux, Michel & Mousseau, Vincent & Michel, Stéphane & Ceugniet, Xavier, 2018. "A compact optimization model for the tail assignment problem," European Journal of Operational Research, Elsevier, vol. 264(2), pages 548-557.
    7. Niklas Kohl & Stefan Karisch, 2004. "Airline Crew Rostering: Problem Types, Modeling, and Optimization," Annals of Operations Research, Springer, vol. 127(1), pages 223-257, March.
    8. N Jozefowiez & C Mancel & F Mora-Camino, 2013. "A heuristic approach based on shortest path problems for integrated flight, aircraft, and passenger rescheduling under disruptions," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 64(3), pages 384-395, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jiang, Jianlin & Zhang, Sijia & Tang, Yucong & Guo, Yuzhen & Wu, Cheng-Lung, 2025. "ADMM-based augmented Lagrangian methods for robust aircraft recovery problem considering connection time, resource capacity and maintenance flexibility," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 201(C).
    2. Breugem, T. & van Rossum, B.T.C. & Dollevoet, T. & Huisman, D., 2022. "A column generation approach for the integrated crew re-planning problem," Omega, Elsevier, vol. 107(C).
    3. Korte, Johanna P. & Yorke-Smith, Neil, 2025. "An aircraft and schedule integrated approach to crew scheduling for a point-to-point airline," Journal of Air Transport Management, Elsevier, vol. 124(C).
    4. Xu, Yifan & Adler, Nicole & Wandelt, Sebastian & Sun, Xiaoqian, 2024. "Competitive integrated airline schedule design and fleet assignment," European Journal of Operational Research, Elsevier, vol. 314(1), pages 32-50.
    5. Zhou, Tianwei & He, Pengcheng & Dai, Weibin & Liu, Ziheng & Gao, Changlong & Huang, Yumiao & Chen, Huan & Geng, Yankun & Niu, Ben, 2026. "Integrated recovery of air cargo transportation under various abnormal scenarios," European Journal of Operational Research, Elsevier, vol. 329(3), pages 864-877.
    6. Philippe Racette & Frédéric Quesnel & Andrea Lodi & François Soumis, 2024. "Gaining insight into crew rostering instances through ML-based sequential assignment," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 32(3), pages 537-578, October.
    7. Zeren, Bahadır & Özcan, Ender & Deveci, Muhammet, 2024. "An adaptive greedy heuristic for large scale airline crew pairing problems," Journal of Air Transport Management, Elsevier, vol. 114(C).
    8. Naz Yeti̇moğlu, Yücel & Selim Aktürk, M., 2021. "Aircraft and passenger recovery during an aircraft’s unexpected unavailability," Journal of Air Transport Management, Elsevier, vol. 91(C).
    9. Wen, Xin & Sun, Xuting & Sun, Yige & Yue, Xiaohang, 2021. "Airline crew scheduling: Models and algorithms," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
    10. Atoosa Kasirzadeh & Mohammed Saddoune & François Soumis, 2017. "Airline crew scheduling: models, algorithms, and data sets," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 6(2), pages 111-137, June.
    11. Guy Desaulniers & François Lessard & Mohammed Saddoune & François Soumis, 2020. "Dynamic Constraint Aggregation for Solving Very Large-scale Airline Crew Pairing Problems," SN Operations Research Forum, Springer, vol. 1(3), pages 1-23, September.
    12. Wen, Xin & Ma, Hoi-Lam & Li, Yantong & He, Yonghuan, 2025. "Do costs and team-building conflict in airline crew scheduling? An individual crew pairing approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 202(C).
    13. Liang Lu & Yanfei Xu & Wei Fan & Haiying Pan & Waihung Ip & Kai Leung Yung, 2025. "Research on the recovery method of disrupted flights considering passenger transfer and cancellation costs," Operations Management Research, Springer, vol. 18(2), pages 691-717, June.
    14. Glomb, Lukas & Liers, Frauke & Rösel, Florian, 2023. "Optimizing integrated aircraft assignment and turnaround handling," European Journal of Operational Research, Elsevier, vol. 310(3), pages 1051-1071.
    15. Schrotenboer, Albert H. & Wenneker, Rob & Ursavas, Evrim & Zhu, Stuart X., 2023. "Reliable reserve-crew scheduling for airlines," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 178(C).
    16. Huang, Lei & Xiao, Fan & Zhou, Jing & Duan, Zhenya & Zhang, Hua & Liang, Zhe, 2023. "A machine learning based column-and-row generation approach for integrated air cargo recovery problem," Transportation Research Part B: Methodological, Elsevier, vol. 178(C).
    17. Abdelghany, Ahmed & Abdelghany, Khaled, 2026. "Addressing the systemic complexity of airline irregular operations: Toward integrated schedule recovery," Journal of Air Transport Management, Elsevier, vol. 131(C).
    18. Quesnel, Frédéric & Desaulniers, Guy & Soumis, François, 2020. "A branch-and-price heuristic for the crew pairing problem with language constraints," European Journal of Operational Research, Elsevier, vol. 283(3), pages 1040-1054.
    19. Maenhout, Broos & Vanhoucke, Mario, 2010. "A hybrid scatter search heuristic for personalized crew rostering in the airline industry," European Journal of Operational Research, Elsevier, vol. 206(1), pages 155-167, October.
    20. Nianyi Wang & Huiling Wang & Shan Pei & Boyu Zhang, 2023. "A Data-Driven Heuristic Method for Irregular Flight Recovery," Mathematics, MDPI, vol. 11(11), pages 1-22, June.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:orinte:v:56:y:2026:i:1:p:58-75. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.