[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v9y2021i17p2138-d627804.html
   My bibliography  Save this article

Dynamic Model of Contingency Flight Crew Planning Extending to Crew Formation

Author

Listed:
  • Vojtech Graf

    (Institute of Transport, Faculty of Mechanical Engineering, VSB—Technical University of Ostrava, 17. Listopadu, 15/2172, 708 00 Ostrava-Poruba, Czech Republic)

  • Dusan Teichmann

    (Institute of Transport, Faculty of Mechanical Engineering, VSB—Technical University of Ostrava, 17. Listopadu, 15/2172, 708 00 Ostrava-Poruba, Czech Republic)

  • Michal Dorda

    (Institute of Transport, Faculty of Mechanical Engineering, VSB—Technical University of Ostrava, 17. Listopadu, 15/2172, 708 00 Ostrava-Poruba, Czech Republic)

  • Lenka Kontrikova

    (Institute of Transport, Faculty of Mechanical Engineering, VSB—Technical University of Ostrava, 17. Listopadu, 15/2172, 708 00 Ostrava-Poruba, Czech Republic)

Abstract
The creation of a flight schedule and the associated crew planning are clearly among the most complicated tasks in terms of traffic preparation. Even with a relatively small number of pilots and aircraft, numerous specific constraints arising from real operations must be included in the calculation, thus increasing the complexity of the planning process. However, even in a precision-planned operation, non-standard situations often occur, which must be addressed flexibly. It is at this point that an operational solution must be applied, the aims of which are to stabilize the flight schedule as soon as possible and minimize the financial impacts resulting from the non-standard situation. These problems are resolved by the airline’s Operational Control Center, which also uses various software approaches to solve the problem. The problem is approached differently by large air carriers, which use software products to address it, and small and medium-sized air carriers, which resolve the issue of operational rescheduling intuitively, based on the experience of dispatchers. However, this intuitive approach can lead to inaccuracies that can lead to unnecessary financial losses. In this paper, we present an optimization model that can serve as a tool to support the decision-making of employees of the operations centers of smaller and medium-sized air carriers.

Suggested Citation

  • Vojtech Graf & Dusan Teichmann & Michal Dorda & Lenka Kontrikova, 2021. "Dynamic Model of Contingency Flight Crew Planning Extending to Crew Formation," Mathematics, MDPI, vol. 9(17), pages 1-28, September.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:17:p:2138-:d:627804
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/9/17/2138/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/9/17/2138/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Saddoune, Mohammed & Desaulniers, Guy & Elhallaoui, Issmail & Soumis, François, 2011. "Integrated airline crew scheduling: A bi-dynamic constraint aggregation method using neighborhoods," European Journal of Operational Research, Elsevier, vol. 212(3), pages 445-454, August.
    2. Frédéric Quesnel & Guy Desaulniers & Frédéric Quesnel, 2020. "Improving Air Crew Rostering by Considering Crew Preferences in the Crew Pairing Problem," Transportation Science, INFORMS, vol. 54(1), pages 97-114, January.
    3. Mohammed Saddoune & Guy Desaulniers & Issmail Elhallaoui & François Soumis, 2012. "Integrated Airline Crew Pairing and Crew Assignment by Dynamic Constraint Aggregation," Transportation Science, INFORMS, vol. 46(1), pages 39-55, February.
    4. Christopher Bayliss & Geert De Maere & Jason A. D. Atkin & Marc Paelinck, 2020. "Scheduling airline reserve crew using a probabilistic crew absence and recovery model," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 71(4), pages 543-565, April.
    5. Da Lu & Fatma Gzara, 2015. "The robust crew pairing problem: model and solution methodology," Journal of Global Optimization, Springer, vol. 62(1), pages 29-54, May.
    6. Ben Ahmed, Mohamed & Zeghal Mansour, Farah & Haouari, Mohamed, 2018. "Robust integrated maintenance aircraft routing and crew pairing," Journal of Air Transport Management, Elsevier, vol. 73(C), pages 15-31.
    7. 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.
    8. Christopher Bayliss & Geert Maere & Jason A. D. Atkin & Marc Paelinck, 2017. "A simulation scenario based mixed integer programming approach to airline reserve crew scheduling under uncertainty," Annals of Operations Research, Springer, vol. 252(2), pages 335-363, May.
    9. Sai Ho Chung & Hoi Lam Ma & Hing Kai Chan, 2017. "Cascading Delay Risk of Airline Workforce Deployments with Crew Pairing and Schedule Optimization," Risk Analysis, John Wiley & Sons, vol. 37(8), pages 1443-1458, August.
    10. Vojtech Graf & Dusan Teichmann & Jiri Horinka & Michal Dorda, 2020. "Dynamic Model for Scheduling Crew Shifts," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-12, May.
    11. Jesica Armas & Luis Cadarso & Angel A. Juan & Javier Faulin, 2017. "A multi-start randomized heuristic for real-life crew rostering problems in airlines with work-balancing goals," Annals of Operations Research, Springer, vol. 258(2), pages 825-848, November.
    12. 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.
    13. 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.
    14. Doi, Tsubasa & Nishi, Tatsushi & Voß, Stefan, 2018. "Two-level decomposition-based matheuristic for airline crew rostering problems with fair working time," European Journal of Operational Research, Elsevier, vol. 267(2), pages 428-438.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xizi Qiao & Ying Yang & Yu Guo & Yong Jin & Shuaian Wang, 2024. "Optimal Routing and Scheduling of Flag State Control Officers in Maritime Transportation," Mathematics, MDPI, vol. 12(11), pages 1-23, May.
    2. Árpád Bűrmen & Tadej Tuma, 2022. "Preface to the Special Issue on “Optimization Theory and Applications”," Mathematics, MDPI, vol. 10(24), pages 1-3, December.
    3. Weihao Ouyang & Xiaohong Zhu, 2023. "Meta-Heuristic Solver with Parallel Genetic Algorithm Framework in Airline Crew Scheduling," Sustainability, MDPI, vol. 15(2), pages 1-21, January.

    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. 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.
    2. 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).
    3. 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).
    4. Ding, Chengjin & Chen, Xinyuan & Wu, Weiwei & Wei, Wenbin & Xin, Zelin, 2023. "Game-theoretic analysis of the impact of crew overnight hotel cost on airlines’ fleet assignment and crew pairing," Journal of Air Transport Management, Elsevier, vol. 113(C).
    5. Wen, Xin & Ma, Hoi-Lam & Chung, Sai-Ho & Khan, Waqar Ahmed, 2020. "Robust airline crew scheduling with flight flying time variability," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 144(C).
    6. Mohamed Haouari & Farah Zeghal Mansour & Hanif D. Sherali, 2019. "A New Compact Formulation for the Daily Crew Pairing Problem," Transportation Science, INFORMS, vol. 53(3), pages 811-828, May.
    7. 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).
    8. Jing-Quan Li, 2014. "Transit Bus Scheduling with Limited Energy," Transportation Science, INFORMS, vol. 48(4), pages 521-539, November.
    9. 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.
    10. 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.
    11. 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).
    12. Sebastian Ruther & Natashia Boland & Faramroze G. Engineer & Ian Evans, 2017. "Integrated Aircraft Routing, Crew Pairing, and Tail Assignment: Branch-and-Price with Many Pricing Problems," Transportation Science, INFORMS, vol. 51(1), pages 177-195, February.
    13. Sai Ho Chung & Hoi Lam Ma & Hing Kai Chan, 2017. "Cascading Delay Risk of Airline Workforce Deployments with Crew Pairing and Schedule Optimization," Risk Analysis, John Wiley & Sons, vol. 37(8), pages 1443-1458, August.
    14. 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.
    15. Vahid Zeighami & François Soumis, 2019. "Combining Benders’ Decomposition and Column Generation for Integrated Crew Pairing and Personalized Crew Assignment Problems," Transportation Science, INFORMS, vol. 53(5), pages 1479-1499, September.
    16. Wen, Xin & Sun, Xuting & Ma, Hoi-Lam & Sun, Yige, 2022. "A column generation approach for operational flight scheduling and aircraft maintenance routing," Journal of Air Transport Management, Elsevier, vol. 105(C).
    17. Birolini, Sebastian & Jacquillat, Alexandre, 2023. "Day-ahead aircraft routing with data-driven primary delay predictions," European Journal of Operational Research, Elsevier, vol. 310(1), pages 379-396.
    18. Qiang Meng & Shuaian Wang & Henrik Andersson & Kristian Thun, 2014. "Containership Routing and Scheduling in Liner Shipping: Overview and Future Research Directions," Transportation Science, INFORMS, vol. 48(2), pages 265-280, May.
    19. Zeighami, Vahid & Saddoune, Mohammed & Soumis, François, 2020. "Alternating Lagrangian decomposition for integrated airline crew scheduling problem," European Journal of Operational Research, Elsevier, vol. 287(1), pages 211-224.
    20. He, Yonghuan & Ma, Hoi-Lam & Park, Woo-Yong & Liu, Shi Qiang & Chung, Sai-Ho, 2023. "Maximizing robustness of aircraft routing with heterogeneous maintenance tasks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 177(C).

    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:gam:jmathe:v:9:y:2021:i:17:p:2138-:d:627804. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.