IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v39y1993i1p115-125.html
   My bibliography  Save this article

Heuristic Algorithms for the Multiple Depot Vehicle Scheduling Problem

Author

Listed:
  • Mauro Dell'Amico

    (DEIS, University of Bologna, Bologna, Italy)

  • Matteo Fischetti

    (DEIS, University of Bologna, Bologna, Italy)

  • Paolo Toth

    (DEIS, University of Bologna, Bologna, Italy)

Abstract

We consider the NP-hard Multiple Depot Vehicle Scheduling Problem, in which a given set of time-tabled trips have to be assigned to vehicles stationed at different depots, so as to minimize the number of vehicles used and the overall operational cost. The problem arises in the management of transportation companies. In this paper some structural properties of the problem are studied and used to design a new polynomial-time heuristic algorithm which always guarantees the use of the minimum number of vehicles. Several effective refining procedures are also proposed. Extensive computational results on test problems involving up to 1,000 trips and 10 depots are reported, showing that the new approach always produces very tight approximate solutions in small computing times and outperforms other heuristics from the literature.

Suggested Citation

  • Mauro Dell'Amico & Matteo Fischetti & Paolo Toth, 1993. "Heuristic Algorithms for the Multiple Depot Vehicle Scheduling Problem," Management Science, INFORMS, vol. 39(1), pages 115-125, January.
    • Handle: RePEc:inm:ormnsc:v:39:y:1993:i:1:p:115-125
    DOI: 10.1287/mnsc.39.1.115
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.39.1.115
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mnsc.39.1.115?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
    ---><---

    Citations

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


    Cited by:

    1. Ciancio, Claudio & Laganà, Demetrio & Musmanno, Roberto & Santoro, Francesco, 2018. "An integrated algorithm for shift scheduling problems for local public transport companies," Omega, Elsevier, vol. 75(C), pages 139-153.
    2. Timo Gschwind & Stefan Irnich & Simon Emde & Christian Tilk, 2018. "Branch-Cut-and-Price for the Scheduling Deliveries with Time Windows in a Direct Shipping Network," Working Papers 1805, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    3. Perumal, Shyam S.G. & Lusby, Richard M. & Larsen, Jesper, 2022. "Electric bus planning & scheduling: A review of related problems and methodologies," European Journal of Operational Research, Elsevier, vol. 301(2), pages 395-413.
    4. Kliewer, Natalia & Mellouli, Taieb & Suhl, Leena, 2006. "A time-space network based exact optimization model for multi-depot bus scheduling," European Journal of Operational Research, Elsevier, vol. 175(3), pages 1616-1627, December.
    5. Desaulniers, Guy & Lavigne, June & Soumis, Francois, 1998. "Multi-depot vehicle scheduling problems with time windows and waiting costs," European Journal of Operational Research, Elsevier, vol. 111(3), pages 479-494, December.
    6. Iris F. A. Vis & René (M.) B. M. de Koster & Martin W. P. Savelsbergh, 2005. "Minimum Vehicle Fleet Size Under Time-Window Constraints at a Container Terminal," Transportation Science, INFORMS, vol. 39(2), pages 249-260, May.
    7. Richard Freling & Albert P. M. Wagelmans & José M. Pinto Paixão, 2001. "Models and Algorithms for Single-Depot Vehicle Scheduling," Transportation Science, INFORMS, vol. 35(2), pages 165-180, May.
    8. Dennis Huisman & Richard Freling & Albert P. M. Wagelmans, 2005. "Multiple-Depot Integrated Vehicle and Crew Scheduling," Transportation Science, INFORMS, vol. 39(4), pages 491-502, November.
    9. Timo Gschwind & Stefan Irnich & Christian Tilk & Simon Emde, 2020. "Branch-cut-and-price for scheduling deliveries with time windows in a direct shipping network," Journal of Scheduling, Springer, vol. 23(3), pages 363-377, June.
    10. Andreas Löbel, 1998. "Vehicle Scheduling in Public Transit and Lagrangean Pricing," Management Science, INFORMS, vol. 44(12-Part-1), pages 1637-1649, December.
    11. Niu, Huimin & Zhou, Xuesong & Tian, Xiaopeng, 2018. "Coordinating assignment and routing decisions in transit vehicle schedules: A variable-splitting Lagrangian decomposition approach for solution symmetry breaking," Transportation Research Part B: Methodological, Elsevier, vol. 107(C), pages 70-101.
    12. Chris Martin & David Jones & Pinar Keskinocak, 2003. "Optimizing On-Demand Aircraft Schedules for Fractional Aircraft Operators," Interfaces, INFORMS, vol. 33(5), pages 22-35, October.
    13. Sundararajan Arunapuram & Kamlesh Mathur & Daniel Solow, 2003. "Vehicle Routing and Scheduling with Full Truckloads," Transportation Science, INFORMS, vol. 37(2), pages 170-182, May.
    14. Uçar, Ezgi & İlker Birbil, Ş. & Muter, İbrahim, 2017. "Managing disruptions in the multi-depot vehicle scheduling problem," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 249-269.
    15. Matteo Fischetti & Andrea Lodi & Silvano Martello & Paolo Toth, 2001. "A Polyhedral Approach to Simplified Crew Scheduling and Vehicle Scheduling Problems," Management Science, INFORMS, vol. 47(6), pages 833-850, June.
    16. Kulkarni, Sarang & Krishnamoorthy, Mohan & Ranade, Abhiram & Ernst, Andreas T. & Patil, Rahul, 2018. "A new formulation and a column generation-based heuristic for the multiple depot vehicle scheduling problem," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 457-487.
    17. Knut Haase & Guy Desaulniers & Jacques Desrosiers, 2001. "Simultaneous Vehicle and Crew Scheduling in Urban Mass Transit Systems," Transportation Science, INFORMS, vol. 35(3), pages 286-303, August.
    18. Ricard, Léa & Desaulniers, Guy & Lodi, Andrea & Rousseau, Louis-Martin, 2024. "Increasing schedule reliability in the multiple depot vehicle scheduling problem with stochastic travel time," Omega, Elsevier, vol. 127(C).
    19. Johanns, Patrick & Lowe, Tim & Plante, Robert, 2001. "Selection and sequencing heuristics to reduce variance in gas turbine engine nozzle assemblies," European Journal of Operational Research, Elsevier, vol. 132(3), pages 490-504, August.
    20. Vis, Iris F.A., 2006. "Survey of research in the design and control of automated guided vehicle systems," European Journal of Operational Research, Elsevier, vol. 170(3), pages 677-709, May.
    21. Li, Jing-Quan & Borenstein, Denis & Mirchandani, Pitu B., 2008. "Truck scheduling for solid waste collection in the City of Porto Alegre, Brazil," Omega, Elsevier, vol. 36(6), pages 1133-1149, December.

    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:ormnsc:v:39:y:1993:i:1:p:115-125. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.