IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v267y2018i2p428-438.html
   My bibliography  Save this article

Two-level decomposition-based matheuristic for airline crew rostering problems with fair working time

Author

Listed:
  • Doi, Tsubasa
  • Nishi, Tatsushi
  • Voß, Stefan

Abstract

We propose a two-level decomposition-based matheuristic algorithm to solve a practical airline crew rostering problem with fair working time. The goal is to find an optimal assignment of pairings to individual crew members that satisfies hard constraints reflecting, for instance, international flights, rest days and regulatory requirements. The objective is to achieve a fair working time of crew members. We propose a two-level decomposition algorithm applying partial optimization under special intensification conditions (POPMUSIC). The method decomposes the original problem into a master problem and a subproblem. The master problem determines an assignment of pairings and rest days. The subproblem checks the feasibility of the original problem when the solution of the master problem is fixed. These problems are iteratively solved by embedding cuts into the master problem. A new method for solving the master problem by a generalized set partitioning reformulation is proposed. The effectiveness of the proposed method for real-world data is shown via computational experiments.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:ejores:v:267:y:2018:i:2:p:428-438
    DOI: 10.1016/j.ejor.2017.11.046
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221717310573
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Souai, Nadia & Teghem, Jacques, 2009. "Genetic algorithm based approach for the integrated airline crew-pairing and rostering problem," European Journal of Operational Research, Elsevier, vol. 199(3), pages 674-683, December.
    2. 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.
    3. Van den Bergh, Jorne & Beliën, Jeroen & De Bruecker, Philippe & Demeulemeester, Erik & De Boeck, Liesje, 2013. "Personnel scheduling: A literature review," European Journal of Operational Research, Elsevier, vol. 226(3), pages 367-385.
    4. 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.
    5. Medard, Claude P. & Sawhney, Nidhi, 2007. "Airline crew scheduling from planning to operations," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1013-1027, December.
    6. Alvim, Adriana C.F. & Taillard, Éric D., 2009. "POPMUSIC for the point feature label placement problem," European Journal of Operational Research, Elsevier, vol. 192(2), pages 396-413, January.
    7. 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.
    8. Federico Della Croce & Fabio Salassa, 2014. "A variable neighborhood search based matheuristic for nurse rostering problems," Annals of Operations Research, Springer, vol. 218(1), pages 185-199, July.
    9. Michel Gamache & François Soumis & Gérald Marquis & Jacques Desrosiers, 1999. "A Column Generation Approach for Large-Scale Aircrew Rostering Problems," Operations Research, INFORMS, vol. 47(2), pages 247-263, April.
    10. Panta Lučić & Dušan Teodorović, 2007. "Metaheuristics approach to the aircrew rostering problem," Annals of Operations Research, Springer, vol. 155(1), pages 311-338, November.
    11. 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.
    12. Guo, Yufeng & Mellouli, Taieb & Suhl, Leena & Thiel, Markus P., 2006. "A partially integrated airline crew scheduling approach with time-dependent crew capacities and multiple home bases," European Journal of Operational Research, Elsevier, vol. 171(3), pages 1169-1181, June.
    13. 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.
    14. Nishi, Tatsushi & Sugiyama, Taichi & Inuiguchi, Masahiro, 2014. "Two-level decomposition algorithm for crew rostering problems with fair working condition," European Journal of Operational Research, Elsevier, vol. 237(2), pages 465-473.
    15. Stolletz, Raik & Brunner, Jens O., 2012. "Fair optimization of fortnightly physician schedules with flexible shifts," European Journal of Operational Research, Elsevier, vol. 219(3), pages 622-629.
    16. B. Maenhout & M. Vanhoucke, 2007. "A Hybrid Scatter Search Heuristic for Personalized Crew Rostering in the Airline Industry," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 07/454, Ghent University, Faculty of Economics and Business Administration.
    17. 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.
    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. Peng, Ling & Kloeden, Peter E., 2021. "Time-consistent portfolio optimization," European Journal of Operational Research, Elsevier, vol. 288(1), pages 183-193.
    2. Wolbeck, Lena Antonia, 2019. "Fairness aspects in personnel scheduling," Discussion Papers 2019/16, Free University Berlin, School of Business & Economics.
    3. 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.
    4. Lai, David S.W. & Leung, Janny M.Y. & Dullaert, Wout & Marques, Inês, 2020. "A graph-based formulation for the shift rostering problem," European Journal of Operational Research, Elsevier, vol. 284(1), pages 285-300.

    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. 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. Atoosa Kasirzadeh & Mohammed Saddoune & François Soumis, 0. "Airline crew scheduling: models, algorithms, and data sets," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 0, pages 1-27.
    3. 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.
    4. 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.
    5. Breugem, T. & Dollevoet, T.A.B. & Huisman, D., 2017. "Is Equality always desirable?," Econometric Institute Research Papers EI2017-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. 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.
    7. Lin, Shih-Wei & Ying, Kuo-Ching, 2014. "Minimizing shifts for personnel task scheduling problems: A three-phase algorithm," European Journal of Operational Research, Elsevier, vol. 237(1), pages 323-334.
    8. Mesquita, Marta & Moz, Margarida & Paias, Ana & Pato, Margarida, 2015. "A decompose-and-fix heuristic based on multi-commodity flow models for driver rostering with days-off pattern," European Journal of Operational Research, Elsevier, vol. 245(2), pages 423-437.
    9. Nishi, Tatsushi & Sugiyama, Taichi & Inuiguchi, Masahiro, 2014. "Two-level decomposition algorithm for crew rostering problems with fair working condition," European Journal of Operational Research, Elsevier, vol. 237(2), pages 465-473.
    10. De Bruecker, Philippe & Van den Bergh, Jorne & Beliën, Jeroen & Demeulemeester, Erik, 2015. "Workforce planning incorporating skills: State of the art," European Journal of Operational Research, Elsevier, vol. 243(1), pages 1-16.
    11. Van den Bergh, Jorne & Beliën, Jeroen & De Bruecker, Philippe & Demeulemeester, Erik & De Boeck, Liesje, 2013. "Personnel scheduling: A literature review," European Journal of Operational Research, Elsevier, vol. 226(3), pages 367-385.
    12. Melanie Erhard, 2021. "Flexible staffing of physicians with column generation," Flexible Services and Manufacturing Journal, Springer, vol. 33(1), pages 212-252, March.
    13. Fuentes, Manuel & Cadarso, Luis & Marín, Ángel, 2019. "A hybrid model for crew scheduling in rail rapid transit networks," Transportation Research Part B: Methodological, Elsevier, vol. 125(C), pages 248-265.
    14. Damcı-Kurt, Pelin & Zhang, Minjiao & Marentay, Brian & Govind, Nirmal, 2019. "Improving physician schedules by leveraging equalization: Cases from hospitals in U.S," Omega, Elsevier, vol. 85(C), pages 182-193.
    15. Wolbeck, Lena Antonia, 2019. "Fairness aspects in personnel scheduling," Discussion Papers 2019/16, Free University Berlin, School of Business & Economics.
    16. De Bruecker, Philippe & Beliën, Jeroen & Van den Bergh, Jorne & Demeulemeester, Erik, 2018. "A three-stage mixed integer programming approach for optimizing the skill mix and training schedules for aircraft maintenance," European Journal of Operational Research, Elsevier, vol. 267(2), pages 439-452.
    17. Panta Lučić & Dušan Teodorović, 2007. "Metaheuristics approach to the aircrew rostering problem," Annals of Operations Research, Springer, vol. 155(1), pages 311-338, November.
    18. 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.
    19. Heil, Julia & Hoffmann, Kirsten & Buscher, Udo, 2020. "Railway crew scheduling: Models, methods and applications," European Journal of Operational Research, Elsevier, vol. 283(2), pages 405-425.
    20. Wolbeck, Lena & Kliewer, Natalia & Marques, Inês, 2020. "Fair shift change penalization scheme for nurse rescheduling problems," European Journal of Operational Research, Elsevier, vol. 284(3), pages 1121-1135.

    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:eee:ejores:v:267:y:2018:i:2:p:428-438. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Nithya Sathishkumar). General contact details of provider: http://www.elsevier.com/locate/eor .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.