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Flight Attendant Rostering for Short-Haul Airline Operations

Author

Listed:
  • Paul R. Day

    (University of Auckland, Auckland, New Zealand)

  • David M. Ryan

    (University of Auckland, Auckland, New Zealand)

Abstract

The construction of flight attendant (cabin crew) rosters for short-haul (domestic) airline flight services that satisfies rostering constraints and employment contract regulations is a combinatorially complex problem. In this paper the problem is described and an effective optimisation-based solution method is introduced. The rostering problem involves the allocation of days-off and various duties to each crew member over a roster period. The days-off and the duty allocation problems are separated into two distinct subproblems. The days-off allocation solution approach involves complete enumeration of all possible days-off lines for each crew member over the roster period, and then the solution of a set partitioning optimisation to determine a best quality feasible days-off roster . The duty allocation solution approach first involves the generation of many lines-of-work consistent with the days-off solution for each crew member over a subroster period and then the solution of a set partitioning optimisation to determine an optimal feasible subroster. These two steps of generation and optimisation are repeated for each subsequent subroster period until a full legal and feasible roster is constructed for the complete roster period. The use of subrosters reduces the combinatorial complexity resulting in problems that can be solved efficiently. After construction of the initial roster, the quality can often be improved using re-rostering techniques. The method leads to efficient construction of good quality legal rosters, and has been used to produce all short-haul flight attendant rosters at Air New Zealand since 1993.

Suggested Citation

  • Paul R. Day & David M. Ryan, 1997. "Flight Attendant Rostering for Short-Haul Airline Operations," Operations Research, INFORMS, vol. 45(5), pages 649-661, October.
  • Handle: RePEc:inm:oropre:v:45:y:1997:i:5:p:649-661
    DOI: 10.1287/opre.45.5.649
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    Citations

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    Cited by:

    1. 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.
    2. Freling, R. & Lentink, R.M. & Wagelmans, A.P.M., 2001. "A decision support system for crew planning in passenger transportation using a flexible branch-and-price algorithm," ERIM Report Series Research in Management ERS-2001-57-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    3. Panta Lučić & Dušan Teodorović, 2007. "Metaheuristics approach to the aircrew rostering problem," Annals of Operations Research, Springer, vol. 155(1), pages 311-338, November.
    4. Cynthia Barnhart & Amy Cohn, 2004. "Airline Schedule Planning: Accomplishments and Opportunities," Manufacturing & Service Operations Management, INFORMS, vol. 6(1), pages 3-22, November.
    5. Chang, Shaw Ching, 2002. "A new aircrew-scheduling model for short-haul routes," Journal of Air Transport Management, Elsevier, vol. 8(4), pages 249-260.
    6. Sophie Veldhoven & Gerhard Post & Egbert Veen & Tim Curtois, 2016. "An assessment of a days off decomposition approach to personnel shift scheduling," Annals of Operations Research, Springer, vol. 239(1), pages 207-223, April.
    7. Xu, Jiefeng & Sohoni, Milind & McCleery, Mike & Bailey, T. Glenn, 2006. "A dynamic neighborhood based tabu search algorithm for real-world flight instructor scheduling problems," European Journal of Operational Research, Elsevier, vol. 169(3), pages 978-993, March.
    8. E. Rod Butchers & Paul R. Day & Andrew P. Goldie & Stephen Miller & Jeff A. Meyer & David M. Ryan & Amanda C. Scott & Chris A. Wallace, 2001. "Optimized Crew Scheduling at Air New Zealand," Interfaces, INFORMS, vol. 31(1), pages 30-56, February.
    9. Ernst, A. T. & Jiang, H. & Krishnamoorthy, M. & Sier, D., 2004. "Staff scheduling and rostering: A review of applications, methods and models," European Journal of Operational Research, Elsevier, vol. 153(1), pages 3-27, February.
    10. Pastor, Rafael & Olivella, Jordi, 2008. "Selecting and adapting weekly work schedules with working time accounts: A case of a retail clothing chain," European Journal of Operational Research, Elsevier, vol. 184(1), pages 1-12, January.
    11. Allen Holder, 2005. "Navy Personnel Planning and the Optimal Partition," Operations Research, INFORMS, vol. 53(1), pages 77-89, February.
    12. J W Hearne, 2007. "A market-driven approach to the optimal stocking problem on African game ranches," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(4), pages 423-428, April.
    13. Nissen, Rüdiger & Haase, Knut, 2004. "Duty-period-based network model for airline crew rescheduling," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 581, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    14. Michael J. Brusco & Larry W. Jacobs, 2000. "Optimal Models for Meal-Break and Start-Time Flexibility in Continuous Tour Scheduling," Management Science, INFORMS, vol. 46(12), pages 1630-1641, December.
    15. Heykel Achour & Michel Gamache & François Soumis & Guy Desaulniers, 2007. "An Exact Solution Approach for the Preferential Bidding System Problem in the Airline Industry," Transportation Science, INFORMS, vol. 41(3), pages 354-365, August.
    16. Cynthia Barnhart & Peter Belobaba & Amedeo R. Odoni, 2003. "Applications of Operations Research in the Air Transport Industry," Transportation Science, INFORMS, vol. 37(4), pages 368-391, November.
    17. 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.

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