IDEAS home Printed from https://ideas.repec.org/a/inm/ortrsc/v44y2010i4p455-473.html
   My bibliography  Save this article

European Driver Rules in Vehicle Routing with Time Windows

Author

Listed:
  • Eric Prescott-Gagnon

    (École Polytechnique de Montréal, Montréal, Québec H3C 3A7, Canada, and GERAD, Montréal, Québec H3T 2A7, Canada)

  • Guy Desaulniers

    (École Polytechnique de Montréal, Montréal, Québec H3C 3A7, Canada, and GERAD, Montréal, Québec H3T 2A7, Canada)

  • Michael Drexl

    (Fraunhofer-Centre for Applied Research on Supply Chain Services SCS, 90411 Nuremberg, Germany)

  • Louis-Martin Rousseau

    (École Polytechnique de Montréal and CIRRELT, Montréal, Québec H3C 3AT, Canada)

Abstract

As of April 2007, the European Union has new regulations concerning driver working hours. These rules force the placement of breaks and rests into vehicle routes when consecutive driving or working time exceeds certain limits. This paper proposes a large neighborhood search method for the vehicle routing problem with time windows and driver regulations. In this method, neighborhoods are explored using a column generation heuristic that relies on a tabu search algorithm for generating new columns (routes). Checking route feasibility after inserting a customer into a route in the tabu search algorithm is not an easy task. To do so, we model all feasibility rules as resource constraints, develop a label-setting algorithm to perform this check, and show how it can be used efficiently to validate multiple customer insertions into a given existing route. We test the overall solution method on modified Solomon instances and report computational results that clearly show the efficiency of our method compared to two other existing heuristics.

Suggested Citation

  • Eric Prescott-Gagnon & Guy Desaulniers & Michael Drexl & Louis-Martin Rousseau, 2010. "European Driver Rules in Vehicle Routing with Time Windows," Transportation Science, INFORMS, vol. 44(4), pages 455-473, November.
    • Handle: RePEc:inm:ortrsc:v:44:y:2010:i:4:p:455-473
    DOI: 10.1287/trsc.1100.0328
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/trsc.1100.0328
    Download Restriction: no
    File URL: https://libkey.io/10.1287/trsc.1100.0328?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
    ---><---

    References listed on IDEAS

    as
    1. Olli Bräysy & Michel Gendreau, 2005. "Vehicle Routing Problem with Time Windows, Part I: Route Construction and Local Search Algorithms," Transportation Science, INFORMS, vol. 39(1), pages 104-118, February.
    2. Martin Savelsbergh & Marc Sol, 1998. "Drive: Dynamic Routing of Independent Vehicles," Operations Research, INFORMS, vol. 46(4), pages 474-490, August.
    3. Brian Kallehauge & Jesper Larsen & Oli B.G. Madsen & Marius M. Solomon, 2005. "Vehicle Routing Problem with Time Windows," Springer Books, in: Guy Desaulniers & Jacques Desrosiers & Marius M. Solomon (ed.), Column Generation, chapter 0, pages 67-98, Springer.
    4. Olli Bräysy & Michel Gendreau, 2005. "Vehicle Routing Problem with Time Windows, Part II: Metaheuristics," Transportation Science, INFORMS, vol. 39(1), pages 119-139, February.
    5. Claudia Archetti & Martin Savelsbergh, 2009. "The Trip Scheduling Problem," Transportation Science, INFORMS, vol. 43(4), pages 417-431, November.
    6. Asvin Goel, 2009. "Vehicle Scheduling and Routing with Drivers' Working Hours," Transportation Science, INFORMS, vol. 43(1), pages 17-26, February.
    7. Marius M. Solomon, 1987. "Algorithms for the Vehicle Routing and Scheduling Problems with Time Window Constraints," Operations Research, INFORMS, vol. 35(2), pages 254-265, April.
    8. Stefan Irnich & Guy Desaulniers, 2005. "Shortest Path Problems with Resource Constraints," Springer Books, in: Guy Desaulniers & Jacques Desrosiers & Marius M. Solomon (ed.), Column Generation, chapter 0, pages 33-65, Springer.
    Full references (including those not matched with items on IDEAS)

    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. Asvin Goel & Stefan Irnich, 2017. "An Exact Method for Vehicle Routing and Truck Driver Scheduling Problems," Transportation Science, INFORMS, vol. 51(2), pages 737-754, May.
    2. Guy Desaulniers & François Lessard & Ahmed Hadjar, 2008. "Tabu Search, Partial Elementarity, and Generalized k -Path Inequalities for the Vehicle Routing Problem with Time Windows," Transportation Science, INFORMS, vol. 42(3), pages 387-404, August.
    3. S. Irnich, 2008. "A Unified Modeling and Solution Framework for Vehicle Routing and Local Search-Based Metaheuristics," INFORMS Journal on Computing, INFORMS, vol. 20(2), pages 270-287, May.
    4. Nicolas Rincon-Garcia & Ben J. Waterson & Tom J. Cherrett, 2018. "Requirements from vehicle routing software: perspectives from literature, developers and the freight industry," Transport Reviews, Taylor & Francis Journals, vol. 38(1), pages 117-138, January.
    5. Christian Tilk & Asvin Goel, 2019. "Bidirectional labeling for solving vehicle routing and truck driver scheduling problems," Working Papers 1914, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    6. Christian Tilk, 2016. "Branch-and-Price-and-Cut for the Vehicle Routing and Truck Driver Scheduling Problem," Working Papers 1616, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    7. Tilk, Christian & Goel, Asvin, 2020. "Bidirectional labeling for solving vehicle routing and truck driver scheduling problems," European Journal of Operational Research, Elsevier, vol. 283(1), pages 108-124.
    8. Taş, D. & Gendreau, M. & Dellaert, N. & van Woensel, T. & de Kok, A.G., 2014. "Vehicle routing with soft time windows and stochastic travel times: A column generation and branch-and-price solution approach," European Journal of Operational Research, Elsevier, vol. 236(3), pages 789-799.
    9. Lahyani, Rahma & Khemakhem, Mahdi & Semet, Frédéric, 2015. "Rich vehicle routing problems: From a taxonomy to a definition," European Journal of Operational Research, Elsevier, vol. 241(1), pages 1-14.
    10. Liu, Ran & Xie, Xiaolan & Garaix, Thierry, 2014. "Hybridization of tabu search with feasible and infeasible local searches for periodic home health care logistics," Omega, Elsevier, vol. 47(C), pages 17-32.
    11. Yi Zhang & Guowei Hua & T. C. E. Cheng & Juliang Zhang, 2020. "Cold chain distribution: How to deal with node and arc time windows?," Annals of Operations Research, Springer, vol. 291(1), pages 1127-1151, August.
    12. Asvin Goel, 2009. "Vehicle Scheduling and Routing with Drivers' Working Hours," Transportation Science, INFORMS, vol. 43(1), pages 17-26, February.
    13. Said Dabia & Stefan Ropke & Tom van Woensel & Ton De Kok, 2013. "Branch and Price for the Time-Dependent Vehicle Routing Problem with Time Windows," Transportation Science, INFORMS, vol. 47(3), pages 380-396, August.
    14. Alcaraz, Juan J. & Caballero-Arnaldos, Luis & Vales-Alonso, Javier, 2019. "Rich vehicle routing problem with last-mile outsourcing decisions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 129(C), pages 263-286.
    15. Bach, Lukas & Gendreau, Michel & Wøhlk, Sanne, 2015. "Freight railway operator timetabling and engine scheduling," European Journal of Operational Research, Elsevier, vol. 241(2), pages 309-319.
    16. Marie-Eve Rancourt & Jean-François Cordeau & Gilbert Laporte, 2013. "Long-Haul Vehicle Routing and Scheduling with Working Hour Rules," Transportation Science, INFORMS, vol. 47(1), pages 81-107, February.
    17. Vidal, Thibaut & Crainic, Teodor Gabriel & Gendreau, Michel & Prins, Christian, 2013. "Heuristics for multi-attribute vehicle routing problems: A survey and synthesis," European Journal of Operational Research, Elsevier, vol. 231(1), pages 1-21.
    18. Jia, Menglei & Chen, Feng, 2023. "Upward scalable vehicle routing problem of automobile inbound logistics with pickup flexibility," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 177(C).
    19. Hideki Hashimoto & Mutsunori Yagiura & Shinji Imahori & Toshihide Ibaraki, 2013. "Recent progress of local search in handling the time window constraints of the vehicle routing problem," Annals of Operations Research, Springer, vol. 204(1), pages 171-187, April.
    20. Maaike Hoogeboom & Wout Dullaert & David Lai & Daniele Vigo, 2020. "Efficient Neighborhood Evaluations for the Vehicle Routing Problem with Multiple Time Windows," Transportation Science, INFORMS, vol. 54(2), pages 400-416, March.

    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:ortrsc:v:44:y:2010:i:4:p:455-473. 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: 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.