IDEAS home Printed from https://ideas.repec.org/a/inm/ortrsc/v41y2007i1p74-89.html
   My bibliography  Save this article

Territory Planning and Vehicle Dispatching with Driver Learning

Author

Listed:
  • Hongsheng Zhong

    (United Parcel Service, 2311 York Road, Timonium, Maryland 21093)

  • Randolph W. Hall

    (Daniel J. Epstein Department of Industrial and Systems Engineering, University of Southern California, Los Angeles, California 90089)

  • Maged Dessouky

    (Daniel J. Epstein Department of Industrial and Systems Engineering, University of Southern California, Los Angeles, California 90089)

Abstract

This paper investigates the construction of routes for local delivery of packages. The primary objective of this research is to provide realistic models to optimize vehicle dispatching when customer locations and demands vary from day to day while maintaining driver familiarity with their service territories, hence dispatch consistency. The objective of increasing driver familiarity tends to make routes or service territories fixed. On the other hand, to serve varying demand it is advantageous to reassign vehicles/drivers and service territories each day. To balance the trade-offs between these two objectives, we developed the concepts of “cell,” “core area,” and “flex zone,” and created a two-stage vehicle routing model---strategic core area design and operational cell routing---and explicitly evaluated the effect of driver familiarity through the use of learning and forgetting curves.

Suggested Citation

  • Hongsheng Zhong & Randolph W. Hall & Maged Dessouky, 2007. "Territory Planning and Vehicle Dispatching with Driver Learning," Transportation Science, INFORMS, vol. 41(1), pages 74-89, February.
  • Handle: RePEc:inm:ortrsc:v:41:y:2007:i:1:p:74-89
    DOI: 10.1287/trsc.1060.0167
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/trsc.1060.0167
    Download Restriction: no

    File URL: https://libkey.io/10.1287/trsc.1060.0167?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. Gendreau, Michel & Laporte, Gilbert & Seguin, Rene, 1996. "Stochastic vehicle routing," European Journal of Operational Research, Elsevier, vol. 88(1), pages 3-12, January.
    2. Hall, Randolph W., 1996. "Pickup and delivery systems for overnight carriers," Transportation Research Part A: Policy and Practice, Elsevier, vol. 30(3), pages 173-187, May.
    3. 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.
    4. Dimitris J. Bertsimas, 1992. "A Vehicle Routing Problem with Stochastic Demand," Operations Research, INFORMS, vol. 40(3), pages 574-585, June.
    5. Haughton, Michael A., 1998. "The performance of route modification and demand stabilization strategies in stochastic vehicle routing," Transportation Research Part B: Methodological, Elsevier, vol. 32(8), pages 551-566, November.
    6. Laguna, Manuel & Kelly, James P. & Gonzalez-Velarde, JoseLuis & Glover, Fred, 1995. "Tabu search for the multilevel generalized assignment problem," European Journal of Operational Research, Elsevier, vol. 82(1), pages 176-189, April.
    7. M A Haughton, 2000. "Quantifying the benefits of route reoptimisation under stochastic customer demands," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 51(3), pages 320-332, March.
    8. Wong, KF & Beasley, JE, 1984. "Vehicle routing using fixed delivery areas," Omega, Elsevier, vol. 12(6), pages 591-600.
    9. Potvin, Jean-Yves & Rousseau, Jean-Marc, 1993. "A parallel route building algorithm for the vehicle routing and scheduling problem with time windows," European Journal of Operational Research, Elsevier, vol. 66(3), pages 331-340, May.
    10. Beasley, J. E. & Christofides, N., 1997. "Vehicle routing with a sparse feasibility graph," European Journal of Operational Research, Elsevier, vol. 98(3), pages 499-511, May.
    11. Carlos F. Daganzo, 1984. "The Distance Traveled to Visit N Points with a Maximum of C Stops per Vehicle: An Analytic Model and an Application," Transportation Science, INFORMS, vol. 18(4), pages 331-350, November.
    12. 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.
    13. 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.
    14. Stewart, William R. & Golden, Bruce L., 1983. "Stochastic vehicle routing: A comprehensive approach," European Journal of Operational Research, Elsevier, vol. 14(4), pages 371-385, December.
    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. Haughton, Michael A., 1998. "The performance of route modification and demand stabilization strategies in stochastic vehicle routing," Transportation Research Part B: Methodological, Elsevier, vol. 32(8), pages 551-566, November.
    2. Jinil Han & Chungmok Lee & Sungsoo Park, 2014. "A Robust Scenario Approach for the Vehicle Routing Problem with Uncertain Travel Times," Transportation Science, INFORMS, vol. 48(3), pages 373-390, August.
    3. Alan L. Erera & Juan C. Morales & Martin Savelsbergh, 2010. "The Vehicle Routing Problem with Stochastic Demand and Duration Constraints," Transportation Science, INFORMS, vol. 44(4), pages 474-492, November.
    4. Shahparvari, Shahrooz & Abbasi, Babak & Chhetri, Prem, 2017. "Possibilistic scheduling routing for short-notice bushfire emergency evacuation under uncertainties: An Australian case study," Omega, Elsevier, vol. 72(C), pages 96-117.
    5. Wen-Huei Yang & Kamlesh Mathur & Ronald H. Ballou, 2000. "Stochastic Vehicle Routing Problem with Restocking," Transportation Science, INFORMS, vol. 34(1), pages 99-112, February.
    6. Novaes, Antonio G. N. & Graciolli, Odacir D., 1999. "Designing multi-vehicle delivery tours in a grid-cell format," European Journal of Operational Research, Elsevier, vol. 119(3), pages 613-634, December.
    7. Michel Beuthe, 2011. "Economics of Transport Logistics," Chapters, in: André de Palma & Robin Lindsey & Emile Quinet & Roger Vickerman (ed.), A Handbook of Transport Economics, chapter 11, Edward Elgar Publishing.
    8. Gendreau, Michel & Laporte, Gilbert & Seguin, Rene, 1996. "Stochastic vehicle routing," European Journal of Operational Research, Elsevier, vol. 88(1), pages 3-12, January.
    9. Chardy, Matthieu & Klopfenstein, Olivier, 2012. "Handling uncertainties in vehicle routing problems through data preprocessing," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(3), pages 667-683.
    10. Tatarakis, A. & Minis, I., 2009. "Stochastic single vehicle routing with a predefined customer sequence and multiple depot returns," European Journal of Operational Research, Elsevier, vol. 197(2), pages 557-571, September.
    11. Li, Xiangyong & Tian, Peng & Leung, Stephen C.H., 2010. "Vehicle routing problems with time windows and stochastic travel and service times: Models and algorithm," International Journal of Production Economics, Elsevier, vol. 125(1), pages 137-145, May.
    12. Florio, Alexandre M. & Hartl, Richard F. & Minner, Stefan, 2020. "Optimal a priori tour and restocking policy for the single-vehicle routing problem with stochastic demands," European Journal of Operational Research, Elsevier, vol. 285(1), pages 172-182.
    13. 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.
    14. Luo, Zhixing & Qin, Hu & Zhang, Dezhi & Lim, Andrew, 2016. "Adaptive large neighborhood search heuristics for the vehicle routing problem with stochastic demands and weight-related cost," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 85(C), pages 69-89.
    15. Bertazzi, Luca & Secomandi, Nicola, 2018. "Faster rollout search for the vehicle routing problem with stochastic demands and restocking," European Journal of Operational Research, Elsevier, vol. 270(2), pages 487-497.
    16. Nicola Secomandi, 2001. "A Rollout Policy for the Vehicle Routing Problem with Stochastic Demands," Operations Research, INFORMS, vol. 49(5), pages 796-802, October.
    17. Merve Cengiz Toklu, 2023. "A fuzzy multi-criteria approach based on Clarke and Wright savings algorithm for vehicle routing problem in humanitarian aid distribution," Journal of Intelligent Manufacturing, Springer, vol. 34(5), pages 2241-2261, June.
    18. Chiang, Wen-Chyuan & Russell, Robert & Xu, Xiaojing & Zepeda, David, 2009. "A simulation/metaheuristic approach to newspaper production and distribution supply chain problems," International Journal of Production Economics, Elsevier, vol. 121(2), pages 752-767, October.
    19. Olli Bräysy & Michel Gendreau, 2005. "Vehicle Routing Problem with Time Windows, Part II: Metaheuristics," Transportation Science, INFORMS, vol. 39(1), pages 119-139, February.
    20. Prasanna Balaprakash & Mauro Birattari & Thomas Stützle & Marco Dorigo, 2015. "Estimation-based metaheuristics for the single vehicle routing problem with stochastic demands and customers," Computational Optimization and Applications, Springer, vol. 61(2), pages 463-487, June.

    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:41:y:2007:i:1:p:74-89. 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.