IDEAS home Printed from https://ideas.repec.org/p/hal/wpaper/hal-00591251.html
   My bibliography  Save this paper

Planning and Scheduling Transportation Vehicle fleet in a Congested Traffic Environment

Author

Listed:
  • Laoucine Kerbache

    (GREGH - Groupement de Recherche et d'Etudes en Gestion à HEC - HEC Paris - Ecole des Hautes Etudes Commerciales - CNRS - Centre National de la Recherche Scientifique)

  • Tom van Woensel

Abstract

Transportation is a main component of supply chain competitiveness since it plays a major role in the inbound, inter-facility, and outbound logistics. In this context, assigning and scheduling vehicle routing is a crucial management problem. Despite numerous publications dealing with efficient scheduling methods for vehicle routing, very few addressed the inherent stochastic nature of travel times in this problem. In this paper, a vehicle routing problem with time windows and stochastic travel times due to potential traffic congestion is considered. The approach developed introduces mainly the traffic congestion component based on queueing theory. This is an innovative modeling scheme to capture the stochastic behavior of travel times. A case study is used both to illustrate the appropriateness of the approach as well as to show that time-independent solutions are often unrealistic within a congested traffic environment which is often the case on the european road networks.

Suggested Citation

  • Laoucine Kerbache & Tom van Woensel, 2011. "Planning and Scheduling Transportation Vehicle fleet in a Congested Traffic Environment," Working Papers hal-00591251, HAL.
    • Handle: RePEc:hal:wpaper:hal-00591251
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    References listed on IDEAS

    as
    1. VAN WOENSEL, Tom & CRETEN, Ruth & VANDAELE, Nico J., "undated". "Managing the environmental externalities of traffic logistics: The issue of emissions," Working Papers 2000022, University of Antwerp, Faculty of Business and Economics.
    2. Malandraki, Chryssi & Dial, Robert B., 1996. "A restricted dynamic programming heuristic algorithm for the time dependent traveling salesman problem," European Journal of Operational Research, Elsevier, vol. 90(1), pages 45-55, April.
    3. Laporte, Gilbert, 1992. "The vehicle routing problem: An overview of exact and approximate algorithms," European Journal of Operational Research, Elsevier, vol. 59(3), pages 345-358, June.
    4. Chryssi Malandraki & Mark S. Daskin, 1992. "Time Dependent Vehicle Routing Problems: Formulations, Properties and Heuristic Algorithms," Transportation Science, INFORMS, vol. 26(3), pages 185-200, August.
    5. G. Clarke & J. W. Wright, 1964. "Scheduling of Vehicles from a Central Depot to a Number of Delivery Points," Operations Research, INFORMS, vol. 12(4), pages 568-581, August.
    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. Xiao, Yiyong & Konak, Abdullah, 2016. "The heterogeneous green vehicle routing and scheduling problem with time-varying traffic congestion," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 88(C), pages 146-166.
    2. Van Woensel, T. & Kerbache, L. & Peremans, H. & Vandaele, N., 2008. "Vehicle routing with dynamic travel times: A queueing approach," European Journal of Operational Research, Elsevier, vol. 186(3), pages 990-1007, May.
    3. LECLUYSE, C. & VAN WOENSEL, Tom & PEREMANS, Herbert, 2007. "Vehicle routing with stochastic time-dependent travel times," Working Papers 2007018, University of Antwerp, Faculty of Business and Economics.
    4. 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.
    5. Furini, Fabio & Persiani, Carlo Alfredo & Toth, Paolo, 2016. "The Time Dependent Traveling Salesman Planning Problem in Controlled Airspace," Transportation Research Part B: Methodological, Elsevier, vol. 90(C), pages 38-55.
    6. Almoustafa, Samira & Hanafi, Said & Mladenović, Nenad, 2013. "New exact method for large asymmetric distance-constrained vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 226(3), pages 386-394.
    7. César Rego, 1998. "A Subpath Ejection Method for the Vehicle Routing Problem," Management Science, INFORMS, vol. 44(10), pages 1447-1459, October.
    8. Majsa Ammouriova & Massimo Bertolini & Juliana Castaneda & Angel A. Juan & Mattia Neroni, 2022. "A Heuristic-Based Simulation for an Education Process to Learn about Optimization Applications in Logistics and Transportation," Mathematics, MDPI, vol. 10(5), pages 1-18, March.
    9. Jean-François Cordeau & Gianpaolo Ghiani & Emanuela Guerriero, 2014. "Analysis and Branch-and-Cut Algorithm for the Time-Dependent Travelling Salesman Problem," Transportation Science, INFORMS, vol. 48(1), pages 46-58, February.
    10. Zhang, Zizhen & Qin, Hu & Wang, Kai & He, Huang & Liu, Tian, 2017. "Manpower allocation and vehicle routing problem in non-emergency ambulance transfer service," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 106(C), pages 45-59.
    11. Tsirimpas, P. & Tatarakis, A. & Minis, I. & Kyriakidis, E.G., 2008. "Single vehicle routing with a predefined customer sequence and multiple depot returns," European Journal of Operational Research, Elsevier, vol. 187(2), pages 483-495, June.
    12. Andres Figliozzi, Miguel, 2012. "The time dependent vehicle routing problem with time windows: Benchmark problems, an efficient solution algorithm, and solution characteristics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(3), pages 616-636.
    13. Sandra Zajac, 2018. "On a two-phase solution approach for the bi-objective k-dissimilar vehicle routing problem," Journal of Heuristics, Springer, vol. 24(3), pages 515-550, June.
    14. Ichoua, Soumia & Gendreau, Michel & Potvin, Jean-Yves, 2003. "Vehicle dispatching with time-dependent travel times," European Journal of Operational Research, Elsevier, vol. 144(2), pages 379-396, January.
    15. Liu, Yiming & Roberto, Baldacci & Zhou, Jianwen & Yu, Yang & Zhang, Yu & Sun, Wei, 2023. "Efficient feasibility checks and an adaptive large neighborhood search algorithm for the time-dependent green vehicle routing problem with time windows," European Journal of Operational Research, Elsevier, vol. 310(1), pages 133-155.
    16. 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.
    17. Sun, Peng & Veelenturf, Lucas P. & Dabia, Said & Van Woensel, Tom, 2018. "The time-dependent capacitated profitable tour problem with time windows and precedence constraints," European Journal of Operational Research, Elsevier, vol. 264(3), pages 1058-1073.
    18. Oscar Dominguez & Angel Juan & Barry Barrios & Javier Faulin & Alba Agustin, 2016. "Using biased randomization for solving the two-dimensional loading vehicle routing problem with heterogeneous fleet," Annals of Operations Research, Springer, vol. 236(2), pages 383-404, January.
    19. Ferrer, Laia & Pastor, Rafael & García-Villoria, Alberto, 2009. "Designing salespeople's routes with multiple visits of customers: A case study," International Journal of Production Economics, Elsevier, vol. 119(1), pages 46-54, May.
    20. Petr Kučera, 2012. "Different versions of the savings method for the time limited vehicle routing problem," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 60(7), pages 171-178.

    More about this item

    Keywords

    transportation; vehicle fleet; planning; scheduling; congested traffic;
    All these keywords.

    JEL classification:

    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

    Statistics

    Access and download statistics

    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:hal:wpaper:hal-00591251. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.