IDEAS home Printed from https://ideas.repec.org/a/pal/palcom/v11y2024i1d10.1057_s41599-024-03496-2.html
   My bibliography  Save this article

Optimisation of a multilevel logistics network for prepositioned warehouses under an omni-channel retail model

Author

Listed:
  • Chenxing Li

    (Beijing Jiaotong University)

  • Xianliang Shi

    (Beijing Jiaotong University)

Abstract

A new omni-channel retailing mode, prepositioned warehouses, which developed rapidly in China during the COVID-19 pandemic, was introduced, and a three-level logistics network optimisation model for agricultural products was presented. This study takes into account the characteristics of the omni-channel retail model, which combines the two delivery methods of vehicle delivery and consumer in-store purchase, adds the freshness penalty incurred by fresh agricultural products in the storage process of the prepositioned warehouse, and establishes a mathematical optimisation model of the three-stage logistics network of the prepositioned warehouse that meets the characteristics of omni-channel retailing on the basis of the classical EOQ inventory model. In this work, the shortest delivery time and the smallest total cost are set as the optimisation objectives, and the multi-objective problem is transformed into a single objective through normalisation and linear weighting methods to obtain a mixed-integer optimisation model. This paper solves the problems of site selection for prepositioned warehouses, merchandise replenishment strategies, and optimisation of delivery routes based on data from real cases. Additionally, through sensitivity analysis, the management inspiration of the enterprise is obtained.

Suggested Citation

  • Chenxing Li & Xianliang Shi, 2024. "Optimisation of a multilevel logistics network for prepositioned warehouses under an omni-channel retail model," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.
  • Handle: RePEc:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-03496-2
    DOI: 10.1057/s41599-024-03496-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41599-024-03496-2
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1057/s41599-024-03496-2?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. Guerrero, W.J. & Prodhon, C. & Velasco, N. & Amaya, C.A., 2013. "Hybrid heuristic for the inventory location-routing problem with deterministic demand," International Journal of Production Economics, Elsevier, vol. 146(1), pages 359-370.
    2. Maria Giuffrida & Riccardo Mangiaracina & Giovanni Miragliotta & Sara Perotti & Angela Tumino, 2019. "Modelling the environmental impact of omni-channel purchasing in the apparel industry: the role of logistics," International Journal of Logistics Systems and Management, Inderscience Enterprises Ltd, vol. 34(4), pages 431-456.
    3. Yue Liu & Guang Song, 2024. "Factors Affecting Supply Chain Integration in Omni-Channel Retailing," Sustainability, MDPI, vol. 16(8), pages 1-18, April.
    4. Salhi, Said & Rand, Graham K., 1989. "The effect of ignoring routes when locating depots," European Journal of Operational Research, Elsevier, vol. 39(2), pages 150-156, March.
    5. Fujiwara, Okitsugu & Perera, U. L. J. S. R., 1993. "EOQ models for continuously deteriorating products using linear and exponential penalty costs," European Journal of Operational Research, Elsevier, vol. 70(1), pages 104-114, October.
    6. Yingying Zhang & Yi Chai & Le Ma, 2021. "Research on Multi-Echelon Inventory Optimization for Fresh Products in Supply Chains," Sustainability, MDPI, vol. 13(11), pages 1-15, June.
    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. Tran, Trung Hieu & Nguyen, Thu Ba T. & Le, Hoa Sen T. & Phung, Duc Chinh, 2024. "Formulation and solution technique for agricultural waste collection and transport network design," European Journal of Operational Research, Elsevier, vol. 313(3), pages 1152-1169.
    2. Drexl, Michael & Schneider, Michael, 2015. "A survey of variants and extensions of the location-routing problem," European Journal of Operational Research, Elsevier, vol. 241(2), pages 283-308.
    3. Linjie Chen & Thibaud Monteiro & Tao Wang & Eric Marcon, 2019. "Design of shared unit-dose drug distribution network using multi-level particle swarm optimization," Health Care Management Science, Springer, vol. 22(2), pages 304-317, June.
    4. Prodhon, Caroline & Prins, Christian, 2014. "A survey of recent research on location-routing problems," European Journal of Operational Research, Elsevier, vol. 238(1), pages 1-17.
    5. Lihua Liu & Lai Soon Lee & Hsin-Vonn Seow & Chuei Yee Chen, 2022. "Logistics Center Location-Inventory-Routing Problem Optimization: A Systematic Review Using PRISMA Method," Sustainability, MDPI, vol. 14(23), pages 1-39, November.
    6. Chen Chao & Tian Zhihui & Yao Baozhen, 2019. "Optimization of two-stage location–routing–inventory problem with time-windows in food distribution network," Annals of Operations Research, Springer, vol. 273(1), pages 111-134, February.
    7. Nadizadeh, Ali & Hosseini Nasab, Hasan, 2014. "Solving the dynamic capacitated location-routing problem with fuzzy demands by hybrid heuristic algorithm," European Journal of Operational Research, Elsevier, vol. 238(2), pages 458-470.
    8. Zhang, Ying & Qi, Mingyao & Miao, Lixin & Liu, Erchao, 2014. "Hybrid metaheuristic solutions to inventory location routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 70(C), pages 305-323.
    9. Mommens, Koen & Buldeo Rai, Heleen & van Lier, Tom & Macharis, Cathy, 2021. "Delivery to homes or collection points? A sustainability analysis for urban, urbanised and rural areas in Belgium," Journal of Transport Geography, Elsevier, vol. 94(C).
    10. A. Anaya-Arenas & J. Renaud & A. Ruiz, 2014. "Relief distribution networks: a systematic review," Annals of Operations Research, Springer, vol. 223(1), pages 53-79, December.
    11. Guerrero, W.J. & Prodhon, C. & Velasco, N. & Amaya, C.A., 2013. "Hybrid heuristic for the inventory location-routing problem with deterministic demand," International Journal of Production Economics, Elsevier, vol. 146(1), pages 359-370.
    12. Dong Li & Xiaojun Wang, 2017. "Dynamic supply chain decisions based on networked sensor data: an application in the chilled food retail chain," International Journal of Production Research, Taylor & Francis Journals, vol. 55(17), pages 5127-5141, September.
    13. Liu, Yubin & Ye, Qiming & Escribano-Macias, Jose & Feng, Yuxiang & Candela, Eduardo & Angeloudis, Panagiotis, 2023. "Route planning for last-mile deliveries using mobile parcel lockers: A hybrid q-learning network approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 177(C).
    14. G. Nagy & S. Salhi, 1998. "The many-to-many location-routing problem," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 6(2), pages 261-275, December.
    15. Paolo Gianessi & Laurent Alfandari & Lucas Létocart & Roberto Wolfler Calvo, 2016. "The Multicommodity-Ring Location Routing Problem," Transportation Science, INFORMS, vol. 50(2), pages 541-558, May.
    16. Zhu, Stuart X. & Ursavas, Evrim, 2018. "Design and analysis of a satellite network with direct delivery in the pharmaceutical industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 116(C), pages 190-207.
    17. Loske, Dominic & Klumpp, Matthias, 2021. "Human-AI collaboration in route planning: An empirical efficiency-based analysis in retail logistics," International Journal of Production Economics, Elsevier, vol. 241(C).
    18. Omar Ahumada & J. Villalobos, 2011. "A tactical model for planning the production and distribution of fresh produce," Annals of Operations Research, Springer, vol. 190(1), pages 339-358, October.
    19. Gläser, Sina, 2022. "A waste collection problem with service type option," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1216-1230.
    20. Danışment Vural & Robert F. Dell & Erkan Kose, 2021. "Locating unmanned aircraft systems for multiple missions under different weather conditions," Operational Research, Springer, vol. 21(1), pages 725-744, March.

    More about this item

    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:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-03496-2. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: https://www.nature.com/ .

    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.