IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v273y2019i2p731-739.html
   My bibliography  Save this article

Shared Capacity Routing Problem − An omni-channel retail study

Author

Listed:
  • Paul, Joydeep
  • Agatz, Niels
  • Spliet, Remy
  • Koster, René De

Abstract

More and more retailers allow customers to order goods online and then pick them up in a store. In this setting, these orders are typically served from a dedicated warehouse. This often means that the stores are visited by different vehicles to replenish the store inventory and to supply the pick-up points. Motivated by a collaboration with an omni-channel grocery retailer in the Netherlands, we study how to best share capacity between the routes associated with these different sales channels. As operational constraints prevent jointly planning the routes, we consider the replenishment routes as fixed when planning the routes to serve the pick-up orders. An order can be transferred to the replenishment route, if capacity allows. We consider the problem of deciding which customer orders to transfer and which to deliver directly such that the total costs are minimized. We present an exact and a heuristic approach to solve this problem. Computational experiments on both real-world and artificial instances show that substantial savings can be achieved by sharing vehicle capacity across different channels.

Suggested Citation

  • Paul, Joydeep & Agatz, Niels & Spliet, Remy & Koster, René De, 2019. "Shared Capacity Routing Problem − An omni-channel retail study," European Journal of Operational Research, Elsevier, vol. 273(2), pages 731-739.
  • Handle: RePEc:eee:ejores:v:273:y:2019:i:2:p:731-739
    DOI: 10.1016/j.ejor.2018.08.027
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221718307227
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2018.08.027?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. Bruce L. Golden & Larry Levy & Rakesh Vohra, 1987. "The orienteering problem," Naval Research Logistics (NRL), John Wiley & Sons, vol. 34(3), pages 307-318, June.
    2. Andreas Stenger & Daniele Vigo & Steffen Enz & Michael Schwind, 2013. "An Adaptive Variable Neighborhood Search Algorithm for a Vehicle Routing Problem Arising in Small Package Shipping," Transportation Science, INFORMS, vol. 47(1), pages 64-80, February.
    3. M A Krajewska & H Kopfer & G Laporte & S Ropke & G Zaccour, 2008. "Horizontal cooperation among freight carriers: request allocation and profit sharing," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(11), pages 1483-1491, November.
    4. Fernández, Elena & Roca-Riu, Mireia & Speranza, M. Grazia, 2018. "The Shared Customer Collaboration Vehicle Routing Problem," European Journal of Operational Research, Elsevier, vol. 265(3), pages 1078-1093.
    5. Côté, Jean-François & Potvin, Jean-Yves, 2009. "A tabu search heuristic for the vehicle routing problem with private fleet and common carrier," European Journal of Operational Research, Elsevier, vol. 198(2), pages 464-469, October.
    6. Gansterer, Margaretha & Hartl, Richard F., 2018. "Collaborative vehicle routing: A survey," European Journal of Operational Research, Elsevier, vol. 268(1), pages 1-12.
    7. Small, Kenneth A. & Ng, Chen Feng, 2014. "Optimizing road capacity and type," Economics of Transportation, Elsevier, vol. 3(2), pages 145-157.
    8. M-C Bolduc & J Renaud & F Boctor & G Laporte, 2008. "A perturbation metaheuristic for the vehicle routing problem with private fleet and common carriers," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(6), pages 776-787, June.
    9. Chu, Ching-Wu, 2005. "A heuristic algorithm for the truckload and less-than-truckload problem," European Journal of Operational Research, Elsevier, vol. 165(3), pages 657-667, September.
    10. Alexander Hübner & Andreas Holzapfel & Heinrich Kuhn, 2016. "Distribution systems in omni-channel retailing," Business Research, Springer;German Academic Association for Business Research, vol. 9(2), pages 255-296, August.
    11. J-Y Potvin & M-A Naud, 2011. "Tabu search with ejection chains for the vehicle routing problem with private fleet and common carrier," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(2), pages 326-336, February.
    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. Zhisong Chen & Chaonan Tang & Jianhui Peng, 2023. "Nominal effect vs actual effect: overconfidence in a consignment omnichannel," Electronic Commerce Research, Springer, vol. 23(2), pages 843-876, June.
    2. Haider, Zulqarnain & Hu, Yujie & Charkhgard, Hadi & Himmelgreen, David & Kwon, Changhyun, 2022. "Creating grocery delivery hubs for food deserts at local convenience stores via spatial and temporal consolidation," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    3. Hübner, Alexander & Hense, Jonas & Dethlefs, Christian, 2022. "The revival of retail stores via omnichannel operations: A literature review and research framework," European Journal of Operational Research, Elsevier, vol. 302(3), pages 799-818.
    4. Chen, Xingli & Zhou, Jianheng, 2021. "The complexity analysis and chaos control in omni-channel supply chain with consumer migration and advertising cost sharing," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
    5. Cai, Ya-Jun & Lo, Chris K.Y., 2020. "Omni-channel management in the new retailing era: A systematic review and future research agenda," International Journal of Production Economics, Elsevier, vol. 229(C).
    6. Nie, Pu-yan & Wang, Chan & Wen, Hong-xing, 2021. "Horizontal mergers under uniform resource constraints," Journal of Retailing and Consumer Services, Elsevier, vol. 63(C).
    7. Jiu, Song, 2022. "Robust omnichannel retail operations with the implementation of ship-from-store," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    8. Wang, Xin & Huang, George Q., 2021. "When and how to share first-mile parcel collection service," European Journal of Operational Research, Elsevier, vol. 288(1), pages 153-169.
    9. Paul, Joydeep & Agatz, Niels & Savelsbergh, Martin, 2019. "Optimizing Omni-Channel Fulfillment with Store Transfers," Transportation Research Part B: Methodological, Elsevier, vol. 129(C), pages 381-396.
    10. Azcuy, Irecis & Agatz, Niels & Giesen, Ricardo, 2021. "Designing integrated urban delivery systems using public transport," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 156(C).
    11. Lafkihi, Mariam & Pan, Shenle & Ballot, Eric, 2019. "Freight transportation service procurement: A literature review and future research opportunities in omnichannel E-commerce," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 348-365.
    12. Kong, Ruixiao & Luo, Li & Chen, Liuxin & Keblis, Matthew F., 2020. "The effects of BOPS implementation under different pricing strategies in omnichannel retailing," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    13. Zhisong Chen & Jianhui Peng, 2022. "Should the assembly system with direct omnichannel introduce integrated management service? A game-theoretical modelling study," Electronic Commerce Research, Springer, vol. 22(4), pages 1307-1350, December.

    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. Ziebuhr, Mario & Kopfer, Herbert, 2016. "Solving an integrated operational transportation planning problem with forwarding limitations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 87(C), pages 149-166.
    2. Paul, J. & Agatz, N.A.H. & Spliet, R. & de Koster, M.B.M., 2017. "Shared Capacity Routing Problem – An Omni-channel Retail Study," ERIM Report Series Research in Management ERS-2017-012-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.
    3. Bertazzi, Luca & Bosco, Adamo & Laganà, Demetrio, 2015. "Managing stochastic demand in an Inventory Routing Problem with transportation procurement," Omega, Elsevier, vol. 56(C), pages 112-121.
    4. Annelieke C. Baller & Said Dabia & Wout E. H. Dullaert & Daniele Vigo, 2020. "The Vehicle Routing Problem with Partial Outsourcing," Transportation Science, INFORMS, vol. 54(4), pages 1034-1052, July.
    5. Zhenzhen Zhang & Zhixing Luo & Hu Qin & Andrew Lim, 2019. "Exact Algorithms for the Vehicle Routing Problem with Time Windows and Combinatorial Auction," Transportation Science, INFORMS, vol. 53(2), pages 427-441, March.
    6. Said Dabia & David Lai & Daniele Vigo, 2019. "An Exact Algorithm for a Rich Vehicle Routing Problem with Private Fleet and Common Carrier," Transportation Science, INFORMS, vol. 53(4), pages 986-1000, July.
    7. Andreas Stenger & Daniele Vigo & Steffen Enz & Michael Schwind, 2013. "An Adaptive Variable Neighborhood Search Algorithm for a Vehicle Routing Problem Arising in Small Package Shipping," Transportation Science, INFORMS, vol. 47(1), pages 64-80, February.
    8. Bertazzi, Luca & Maggioni, Francesca, 2018. "A stochastic multi-stage fixed charge transportation problem: Worst-case analysis of the rolling horizon approach," European Journal of Operational Research, Elsevier, vol. 267(2), pages 555-569.
    9. Amiri, Mosleh & Farvaresh, Hamid, 2023. "Carrier collaboration with the simultaneous presence of transferable and non-transferable utilities," European Journal of Operational Research, Elsevier, vol. 304(2), pages 596-617.
    10. Margaretha Gansterer & Murat Küçüktepe & Richard F. Hartl, 2017. "The multi-vehicle profitable pickup and delivery problem," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(1), pages 303-319, January.
    11. Gahm, Christian & Brabänder, Christian & Tuma, Axel, 2017. "Vehicle routing with private fleet, multiple common carriers offering volume discounts, and rental options," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 97(C), pages 192-216.
    12. Thibaut Vidal & Nelson Maculan & Luiz Satoru Ochi & Puca Huachi Vaz Penna, 2016. "Large Neighborhoods with Implicit Customer Selection for Vehicle Routing Problems with Profits," Transportation Science, INFORMS, vol. 50(2), pages 720-734, May.
    13. Nassim Mrabti & Nadia Hamani & Laurent Delahoche, 2022. "A Comprehensive Literature Review on Sustainable Horizontal Collaboration," Sustainability, MDPI, vol. 14(18), pages 1-38, September.
    14. Guajardo, Mario & Rönnqvist, Mikael & Flisberg, Patrik & Frisk, Mikael, 2018. "Collaborative transportation with overlapping coalitions," European Journal of Operational Research, Elsevier, vol. 271(1), pages 238-249.
    15. J-Y Potvin & M-A Naud, 2011. "Tabu search with ejection chains for the vehicle routing problem with private fleet and common carrier," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(2), pages 326-336, February.
    16. Wang, Xin & Kopfer, Herbert & Gendreau, Michel, 2014. "Operational transportation planning of freight forwarding companies in horizontal coalitions," European Journal of Operational Research, Elsevier, vol. 237(3), pages 1133-1141.
    17. 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.
    18. Bulhões, Teobaldo & Hà, Minh Hoàng & Martinelli, Rafael & Vidal, Thibaut, 2018. "The vehicle routing problem with service level constraints," European Journal of Operational Research, Elsevier, vol. 265(2), pages 544-558.
    19. Li, Junsong & Rong, Gang & Feng, Yiping, 2015. "Request selection and exchange approach for carrier collaboration based on auction of a single request," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 84(C), pages 23-39.
    20. Liu, Ran & Jiang, Zhibin, 2012. "The close–open mixed vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 220(2), pages 349-360.

    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:ejores:v:273:y:2019:i:2:p:731-739. 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/locate/eor .

    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.