IDEAS home Printed from https://ideas.repec.org/p/ems/eureri/116065.html

On the Benefits of Flexible Customer-to-Depot Assignments in Attended Home Delivery

Author

Listed:
  • Seifried, K.
  • Agatz, N.A.H.
  • Fleischmann, M.

Abstract

This paper investigates the value of flexibility in customer-to-depot assignments in last-mile distribution operations. In current practice, many companies use fixed delivery regions for their fulfillment warehouses. This allows a decomposition of delivery operations by ware- house, thereby simplifying the planning process. However, this approach foregoes some optimization potential, relative to a holistic planning of the delivery operations across the network. In this paper, we assess the value of this flexibility. We first identify and characterize two specific types of benefits, namely a routing benefit and a pooling benefit. We then proceed to quantify these benefits in an extensive numerical study. Our results disentangle how the benefits depend on key environmental parameters. They also show that a flexible customer-to-depot assignment can add significant value in various relevant conditions.

Suggested Citation

  • Seifried, K. & Agatz, N.A.H. & Fleischmann, M., 2019. "On the Benefits of Flexible Customer-to-Depot Assignments in Attended Home Delivery," ERIM Report Series Research in Management ERS-2019-004-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    • Handle: RePEc:ems:eureri:116065
    as

    Download full text from publisher

    File URL: https://repub.eur.nl/pub/116065/ERS-2019-004-LIS.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dondo, Rodolfo & Cerda, Jaime, 2007. "A cluster-based optimization approach for the multi-depot heterogeneous fleet vehicle routing problem with time windows," European Journal of Operational Research, Elsevier, vol. 176(3), pages 1478-1507, February.
    2. Torabi, S.A. & Hassini, E. & Jeihoonian, M., 2015. "Fulfillment source allocation, inventory transshipment, and customer order transfer in e-tailing," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 79(C), pages 128-144.
    3. Ping Josephine Xu & Russell Allgor & Stephen C. Graves, 2009. "Benefits of Reevaluating Real-Time Order Fulfillment Decisions," Manufacturing & Service Operations Management, INFORMS, vol. 11(2), pages 340-355, January.
    4. Jason Acimovic & Stephen C. Graves, 2015. "Making Better Fulfillment Decisions on the Fly in an Online Retail Environment," Manufacturing & Service Operations Management, INFORMS, vol. 17(1), pages 34-51, February.
    5. J-F Cordeau & G Laporte & A Mercier, 2004. "Improved tabu search algorithm for the handling of route duration constraints in vehicle routing problems with time windows," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(5), pages 542-546, May.
    6. J-F Cordeau & G Laporte & A Mercier, 2001. "A unified tabu search heuristic for vehicle routing problems with time windows," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 52(8), pages 928-936, 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. Puca Huachi Vaz Penna & Anand Subramanian & Luiz Satoru Ochi & Thibaut Vidal & Christian Prins, 2019. "A hybrid heuristic for a broad class of vehicle routing problems with heterogeneous fleet," Annals of Operations Research, Springer, vol. 273(1), pages 5-74, February.
    2. Ehsan Khodabandeh & Lihui Bai & Sunderesh S. Heragu & Gerald W. Evans & Thomas Elrod & Mark Shirkness, 2017. "Modelling and solution of a large-scale vehicle routing problem at GE appliances & lighting," International Journal of Production Research, Taylor & Francis Journals, vol. 55(4), pages 1100-1116, February.
    3. Zhang, Yuankai & Lin, Wei-Hua & Huang, Minfang & Hu, Xiangpei, 2021. "Multi-warehouse package consolidation for split orders in online retailing," European Journal of Operational Research, Elsevier, vol. 289(3), pages 1040-1055.
    4. Li, Shuqin & Jia, Shuai, 2019. "A Benders decomposition algorithm for the order fulfilment problem of an e-tailer with a self-owned logistics system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 463-480.
    5. Zhang, Yuankai & Sun, Lijun & Hu, Xiangpei & Zhao, Chen, 2019. "Order consolidation for the last-mile split delivery in online retailing," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 309-327.
    6. Schmid, Verena & Doerner, Karl F. & Laporte, Gilbert, 2013. "Rich routing problems arising in supply chain management," European Journal of Operational Research, Elsevier, vol. 224(3), pages 435-448.
    7. Qian, Fubin & Gribkovskaia, Irina & Laporte, Gilbert & Halskau sr., Øyvind, 2012. "Passenger and pilot risk minimization in offshore helicopter transportation," Omega, Elsevier, vol. 40(5), pages 584-593.
    8. Shijin Wang & Xiaodong Wang & Xin Liu & Jianbo Yu, 2018. "A Bi-Objective Vehicle-Routing Problem with Soft Time Windows and Multiple Depots to Minimize the Total Energy Consumption and Customer Dissatisfaction," Sustainability, MDPI, vol. 10(11), pages 1-21, November.
    9. Yajun Zhan & Yiping Jiang, 2022. "Integrated Optimization of Order Allocation and Last-Mile Multi-Temperature Joint Distribution for Fresh Agriproduct Community Retail," Sustainability, MDPI, vol. 14(15), pages 1-18, August.
    10. Bochra Rabbouch & Foued Saâdaoui & Rafaa Mraihi, 2021. "Efficient implementation of the genetic algorithm to solve rich vehicle routing problems," Operational Research, Springer, vol. 21(3), pages 1763-1791, September.
    11. Banu Y. Ekren & Sara Perotti & Laura Foresti & Lorenzo Prataviera, 2025. "Enhancing e-grocery order fulfillment: improving product availability, cost, and emissions in last-mile delivery," Electronic Commerce Research, Springer, vol. 25(3), pages 2417-2455, June.
    12. Schneider, Michael, 2016. "The vehicle-routing problem with time windows and driver-specific times," European Journal of Operational Research, Elsevier, vol. 250(1), pages 101-119.
    13. Xueqi Wu & Zhi‐Long Chen, 2022. "Fulfillment scheduling for buy‐online‐pickup‐in‐store orders," Production and Operations Management, Production and Operations Management Society, vol. 31(7), pages 2982-3003, July.
    14. Libo Sun & Guodong Lyu & Yugang Yu & Chung‐Piaw Teo, 2020. "Fulfillment by Amazon versus fulfillment by seller: An interpretable risk‐adjusted fulfillment model," Naval Research Logistics (NRL), John Wiley & Sons, vol. 67(8), pages 627-645, December.
    15. Schneider, M., 2016. "The vehicle-routing problem with time windows and driver-specific times," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 65941, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    16. Vidal, Thibaut & Crainic, Teodor Gabriel & Gendreau, Michel & Prins, Christian, 2014. "A unified solution framework for multi-attribute vehicle routing problems," European Journal of Operational Research, Elsevier, vol. 234(3), pages 658-673.
    17. Stefanus Jasin & Amitabh Sinha, 2015. "An LP-Based Correlated Rounding Scheme for Multi-Item Ecommerce Order Fulfillment," Operations Research, INFORMS, vol. 63(6), pages 1336-1351, December.
    18. Difrancesco, Rita Maria & van Schilt, Isabelle M. & Winkenbach, Matthias, 2021. "Optimal in-store fulfillment policies for online orders in an omni-channel retail environment," European Journal of Operational Research, Elsevier, vol. 293(3), pages 1058-1076.
    19. Ann-Kathrin Rothenbächer, 2019. "Branch-and-Price-and-Cut for the Periodic Vehicle Routing Problem with Flexible Schedule Structures," Transportation Science, INFORMS, vol. 53(3), pages 850-866, May.
    20. Ardjmand, Ehsan & Sanei Bajgiran, Omid & Rahman, Shakil & Weckman, Gary R. & Young, William A., 2018. "A multi-objective model for order cartonization and fulfillment center assignment in the e-tail/retail industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 115(C), pages 16-34.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ems:eureri:116065. 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: RePub The email address of this maintainer does not seem to be valid anymore. Please ask RePub to update the entry or send us the correct address (email available below). General contact details of provider: https://edirc.repec.org/data/erimanl.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.