IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v140y2020icp36-51.html
   My bibliography  Save this article

The long-haul full-load vehicle routing and truck driver scheduling problem with intermediate stops: An economic impact evaluation of Brazilian policy

Author

Listed:
  • Mayerle, Sérgio Fernando
  • De Genaro Chiroli, Daiane Maria
  • Neiva de Figueiredo, João
  • Rodrigues, Hidelbrando Ferreira

Abstract

This paper presents a methodology to identify the economic impact of different policies for heavy vehicle routing and driver scheduling in long-haul full-load trips with intermediate stops for refueling and for regulation-driven meal and rest periods. This methodology can be used both as a planning tool to help policy-makers define policies through scenario simulations, and as an evaluation tool to examine ex-post economic impact once policies have been changed as illustrated herein for the Brazilian case. The paper introduces a mathematical formulation, proposes a state-space graph search approach, and develops an algorithmic solution for a variant of the vehicle routing and truck driver scheduling problem with intermediate stops (VRTDSPIS), which is especially important in countries with vast territory where long-range freight trucking trips are common. In addition, it is particularly relevant for the economies of emerging markets that may have evolving regulatory frameworks and suboptimal infrastructure environments. Regulatory maximum driving and minimum driver resting time windows impose significant constraints to trucker routines, especially in sparsely populated regions through which long range vehicle trips with full load are common. Such trips can take days to be concluded and numerous alternative routes are possible, each with very different alternatives for refueling and rest. While the literature to date has focused mostly on truck driver scheduling given pre-determined routes and individual country’s laws and regulations, this paper proposes a joint solution for the routing and scheduling problem with time window constraints, determining simultaneously a routing and scheduling plan that meets all maximum driving and minimum resting time interval regulatory requirements at minimum cost. An illustration applying the methodology to evaluate the economic impact of truck driver regulatory changes in Brazil is presented.

Suggested Citation

  • Mayerle, Sérgio Fernando & De Genaro Chiroli, Daiane Maria & Neiva de Figueiredo, João & Rodrigues, Hidelbrando Ferreira, 2020. "The long-haul full-load vehicle routing and truck driver scheduling problem with intermediate stops: An economic impact evaluation of Brazilian policy," Transportation Research Part A: Policy and Practice, Elsevier, vol. 140(C), pages 36-51.
    • Handle: RePEc:eee:transa:v:140:y:2020:i:c:p:36-51
    DOI: 10.1016/j.tra.2020.07.021
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965856420306765
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tra.2020.07.021?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. 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. Pelletier, Samuel & Jabali, Ola & Laporte, Gilbert, 2019. "The electric vehicle routing problem with energy consumption uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 126(C), pages 225-255.
    3. Asvin Goel & Thibaut Vidal, 2014. "Hours of Service Regulations in Road Freight Transport: An Optimization-Based International Assessment," Transportation Science, INFORMS, vol. 48(3), pages 391-412, August.
    4. Çağrı Koç & Ola Jabali & Gilbert Laporte, 2018. "Long-haul vehicle routing and scheduling with idling options," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 69(2), pages 235-246, February.
    5. Goel, Asvin, 2018. "Legal aspects in road transport optimization in Europe," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 144-162.
    6. Asvin Goel, 2009. "Vehicle Scheduling and Routing with Drivers' Working Hours," Transportation Science, INFORMS, vol. 43(1), pages 17-26, February.
    7. Martin Savelsbergh & Marc Sol, 1998. "Drive: Dynamic Routing of Independent Vehicles," Operations Research, INFORMS, vol. 46(4), pages 474-490, August.
    8. Alberto Ceselli & Giovanni Righini & Matteo Salani, 2009. "A Column Generation Algorithm for a Rich Vehicle-Routing Problem," Transportation Science, INFORMS, vol. 43(1), pages 56-69, February.
    9. Maximilian Schiffer & Michael Schneider & Grit Walther & Gilbert Laporte, 2019. "Vehicle Routing and Location Routing with Intermediate Stops: A Review," Transportation Science, INFORMS, vol. 53(2), pages 319-343, March.
    10. Wen, Liang & Çatay, Bülent & Eglese, Richard, 2014. "Finding a minimum cost path between a pair of nodes in a time-varying road network with a congestion charge," European Journal of Operational Research, Elsevier, vol. 236(3), pages 915-923.
    11. 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.
    12. 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.
    13. Hang Xu & Zhi-Long Chen & Srinivas Rajagopal & Sundar Arunapuram, 2003. "Solving a Practical Pickup and Delivery Problem," Transportation Science, INFORMS, vol. 37(3), pages 347-364, August.
    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. Nguyen, Phuong H.D. & Tran, Daniel, 2024. "Constraint-Based snowplow optimization model for winter maintenance operations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 179(C).
    2. Hu, Qiaolin & Gu, Weihua & Wu, Lingxiao & Zhang, Le, 2024. "Optimal autonomous truck platooning with detours, nonlinear costs, and a platoon size constraint," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 186(C).
    3. Daiane Maria Genaro Chiroli & Sérgio Fernando Mayerle & João Neiva Figueiredo, 2022. "Using state-space shortest-path heuristics to solve the long-haul point-to-point vehicle routing and driver scheduling problem subject to hours-of-service regulatory constraints," Journal of Heuristics, Springer, vol. 28(1), pages 23-59, February.
    4. Vital, Filipe & Ioannou, Petros, 2021. "Scheduling and shortest path for trucks with working hours and parking availability constraints," Transportation Research Part B: Methodological, Elsevier, vol. 148(C), pages 1-37.

    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. Daiane Maria Genaro Chiroli & Sérgio Fernando Mayerle & João Neiva Figueiredo, 2022. "Using state-space shortest-path heuristics to solve the long-haul point-to-point vehicle routing and driver scheduling problem subject to hours-of-service regulatory constraints," Journal of Heuristics, Springer, vol. 28(1), pages 23-59, February.
    2. 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.
    3. Ostermeier, Manuel, 2024. "The supply of convenience stores: Challenges of short-distance routing within the constraints of working time regulations," European Journal of Operational Research, Elsevier, vol. 314(3), pages 997-1012.
    4. Goel, Asvin, 2018. "Legal aspects in road transport optimization in Europe," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 144-162.
    5. Eskandarzadeh, Saman & Fahimnia, Behnam, 2022. "Rest break policy comparison for heavy vehicle drivers in Australia," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 159(C).
    6. Asvin Goel & Thibaut Vidal & Adrianus Leendert Kok, 2021. "To team up or not: single versus team driving in European road freight transport," Flexible Services and Manufacturing Journal, Springer, vol. 33(4), pages 879-913, December.
    7. 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.
    8. Mor, Andrea & Archetti, Claudia & Jabali, Ola & Simonetto, Alberto & Speranza, M. Grazia, 2022. "The Bi-objective Long-haul Transportation Problem on a Road Network," Omega, Elsevier, vol. 106(C).
    9. Maximilian Schiffer & Michael Schneider & Grit Walther & Gilbert Laporte, 2019. "Vehicle Routing and Location Routing with Intermediate Stops: A Review," Transportation Science, INFORMS, vol. 53(2), pages 319-343, March.
    10. 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.
    11. Koç, Çağrı & Bektaş, Tolga & Jabali, Ola & Laporte, Gilbert, 2016. "A comparison of three idling options in long-haul truck scheduling," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 631-647.
    12. 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.
    13. Pottel, Steffen & Goel, Asvin, 2022. "Scheduling activities with time-dependent durations and resource consumptions," European Journal of Operational Research, Elsevier, vol. 301(2), pages 445-457.
    14. Alcaraz, Juan J. & Losilla, Fernando & Caballero-Arnaldos, Luis, 2022. "Online model-based reinforcement learning for decision-making in long distance routes," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    15. Vidal, Thibaut & Laporte, Gilbert & Matl, Piotr, 2020. "A concise guide to existing and emerging vehicle routing problem variants," European Journal of Operational Research, Elsevier, vol. 286(2), pages 401-416.
    16. 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.
    17. 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.
    18. 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.
    19. Gilbert Laporte, 2016. "Scheduling issues in vehicle routing," Annals of Operations Research, Springer, vol. 236(2), pages 463-474, January.
    20. Vital, Filipe & Ioannou, Petros, 2021. "Scheduling and shortest path for trucks with working hours and parking availability constraints," Transportation Research Part B: Methodological, Elsevier, vol. 148(C), pages 1-37.

    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:transa:v:140:y:2020:i:c:p:36-51. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/547/description#description .

    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.