IDEAS home Printed from https://ideas.repec.org/a/spr/pubtra/v1y2009i3d10.1007_s12469-009-0013-x.html
   My bibliography  Save this article

Bi-objective evolutionary heuristics for bus driver rostering

Author

Listed:
  • Margarida Moz

    (Technical University of Lisbon
    University of Lisbon)

  • Ana Respício

    (University of Lisbon
    University of Lisbon)

  • Margarida Vaz Pato

    (Technical University of Lisbon
    University of Lisbon)

Abstract

The Bus Driver Rostering Problem (BRP) refers to the assignment of drivers to the daily crew duties that cover a set of schedules for buses of a company during a planning period of a given duration, e.g., a month. An assignment such as this, denoted as roster, must comply with legal and institutional rules, namely Labour Law, labour agreements and the company’s regulations. This paper presents a new bi-objective model for the BRP, assuming a non-cyclic rostering context. One such model is appropriate to deal with the specific and diverse requirements of individual drivers, e.g. absences. Two evolutionary heuristics, differing as to the strategies adopted to approach the Pareto frontier, are described for the BRP. The first one, following a utopian strategy, extends elitism to include an infeasible (utopic) and two potential lexicographic individuals in the population, and the second one is an adapted version of the well known SPEA2 (Strength Pareto Evolutionary Algorithm). The heuristics’ empirical performance was studied through computational tests on BRP instances generated from the solution of integrated vehicle-crew scheduling problems, along with the rules of a public transit company operating in Portugal. This research shows that both methodologies are adequate to tackle these instances. However, the second one is, in general, the more favourable. In reasonable computation times they provide the company’s planning department with several rosters that satisfy all the constraints, an achievement which is very difficult to obtain manually. In addition, among these rosters they identify the potentially efficient ones with respect to the BRP model’s two objectives, one concerning the interests of administration, the other the interests of the workers. Both heuristics have advantages and drawbacks. This suggests that they should be used complementarily. On the other hand, the heuristics can, with little effort, be adapted to a wide variety of rostering rules.

Suggested Citation

  • Margarida Moz & Ana Respício & Margarida Vaz Pato, 2009. "Bi-objective evolutionary heuristics for bus driver rostering," Public Transport, Springer, vol. 1(3), pages 189-210, August.
    • Handle: RePEc:spr:pubtra:v:1:y:2009:i:3:d:10.1007_s12469-009-0013-x
    DOI: 10.1007/s12469-009-0013-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12469-009-0013-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s12469-009-0013-x?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
    ---><---

    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. Alberto Caprara & Paolo Toth & Daniele Vigo & Matteo Fischetti, 1998. "Modeling and Solving the Crew Rostering Problem," Operations Research, INFORMS, vol. 46(6), pages 820-830, December.
    2. Richard Freling & Ramon Lentink & Albert Wagelmans, 2004. "A Decision Support System for Crew Planning in Passenger Transportation Using a Flexible Branch-and-Price Algorithm," Annals of Operations Research, Springer, vol. 127(1), pages 203-222, March.
    3. Bianco, Lucio & Bielli, Maurizio & Mingozzi, Aristide & Ricciardelli, Salvatore & Spadoni, Massimo, 1992. "A heuristic procedure for the crew rostering problem," European Journal of Operational Research, Elsevier, vol. 58(2), pages 272-283, April.
    4. M Lezaun & G Pérez & E Sáinz de la Maza, 2006. "Crew rostering problem in a public transport company," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(10), pages 1173-1179, October.
    5. Chu, Sydney C.K., 2007. "Generating, scheduling and rostering of shift crew-duties: Applications at the Hong Kong International Airport," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1764-1778, March.
    6. 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.
    7. Panta Lučić & Dušan Teodorović, 2007. "Metaheuristics approach to the aircrew rostering problem," Annals of Operations Research, Springer, vol. 155(1), pages 311-338, November.
    8. ManMohan Sodhi & Stephen Norris, 2004. "A Flexible, Fast, and Optimal Modeling Approach Applied to Crew Rostering at London Underground," Annals of Operations Research, Springer, vol. 127(1), pages 259-281, March.
    9. Carraresi, P. & Gallo, G., 1984. "A multi-level bottleneck assignment approach to the bus drivers' rostering problem," European Journal of Operational Research, Elsevier, vol. 16(2), pages 163-173, May.
    10. Paola Cappanera & Giorgio Gallo, 2004. "A Multicommodity Flow Approach to the Crew Rostering Problem," Operations Research, INFORMS, vol. 52(4), pages 583-596, August.
    11. Lucic, Panta & Teodorovic, Dusan, 1999. "Simulated annealing for the multi-objective aircrew rostering problem," Transportation Research Part A: Policy and Practice, Elsevier, vol. 33(1), pages 19-45, January.
    12. 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. Safae Er-Rbib & Guy Desaulniers & Issmail Elhallaoui & Patrick Munroe, 2021. "Preference-based and cyclic bus driver rostering problem with fixed days off," Public Transport, Springer, vol. 13(2), pages 251-286, June.
    2. F. Zeynep Sargut & Caner Altuntaş & Dilek Cetin Tulazoğlu, 2017. "Multi-objective integrated acyclic crew rostering and vehicle assignment problem in public bus transportation," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(4), pages 1071-1096, October.

    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. 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.
    2. F. Zeynep Sargut & Caner Altuntaş & Dilek Cetin Tulazoğlu, 2017. "Multi-objective integrated acyclic crew rostering and vehicle assignment problem in public bus transportation," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(4), pages 1071-1096, October.
    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. Panta Lučić & Dušan Teodorović, 2007. "Metaheuristics approach to the aircrew rostering problem," Annals of Operations Research, Springer, vol. 155(1), pages 311-338, November.
    5. 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.
    6. Thomas Breugem & Twan Dollevoet & Dennis Huisman, 2022. "Is Equality Always Desirable? Analyzing the Trade-Off Between Fairness and Attractiveness in Crew Rostering," Management Science, INFORMS, vol. 68(4), pages 2619-2641, April.
    7. Yiting Xing & Ling Li & Zhuming Bi & Marzena Wilamowska‐Korsak & Li Zhang, 2013. "Operations Research (OR) in Service Industries: A Comprehensive Review," Systems Research and Behavioral Science, Wiley Blackwell, vol. 30(3), pages 300-353, May.
    8. 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.
    9. Dennis Huisman & Leo G. Kroon & Ramon M. Lentink & Michiel J. C. M. Vromans, 2005. "Operations Research in passenger railway transportation," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 59(4), pages 467-497, November.
    10. Tallys H. Yunes & Arnaldo V. Moura & Cid C. de Souza, 2005. "Hybrid Column Generation Approaches for Urban Transit Crew Management Problems," Transportation Science, INFORMS, vol. 39(2), pages 273-288, May.
    11. Attila Tóth & Miklós Krész, 2013. "An efficient solution approach for real-world driver scheduling problems in urban bus transportation," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 21(1), pages 75-94, June.
    12. 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.
    13. 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.
    14. Lin Xie & Marius Merschformann & Natalia Kliewer & Leena Suhl, 2017. "Metaheuristics approach for solving personalized crew rostering problem in public bus transit," Journal of Heuristics, Springer, vol. 23(5), pages 321-347, October.
    15. Hartog, A. & Huisman, D. & Abbink, E.J.W. & Kroon, L.G., 2006. "Decision support for crew rostering at NS," Econometric Institute Research Papers EI 2006-04, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    16. Ralf Borndörfer & Guillaume Sagnol & Thomas Schlechte & Elmar Swarat, 2017. "Optimal duty rostering for toll enforcement inspectors," Annals of Operations Research, Springer, vol. 252(2), pages 383-406, May.
    17. 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).
    18. 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.
    19. Emir Hüseyin Özder & Evrencan Özcan & Tamer Eren, 2019. "Staff Task-Based Shift Scheduling Solution with an ANP and Goal Programming Method in a Natural Gas Combined Cycle Power Plant," Mathematics, MDPI, vol. 7(2), pages 1-26, February.
    20. 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.

    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:spr:pubtra:v:1:y:2009:i:3:d:10.1007_s12469-009-0013-x. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.