IDEAS home Printed from https://ideas.repec.org/a/spr/opmare/v18y2025i2d10.1007_s12063-023-00432-6.html
   My bibliography  Save this article

Mixed reality-based online 3D pallet loading problem to achieve augmented intelligence in e-fulfilment processes

Author

Listed:
  • T.T. Yang

    (Queen Mary University of London)

  • Y. P. Tsang

    (The Hong Kong Polytechnic University)

  • C. H. Wu

    (The Hang Seng University of Hong Kong)

  • K. T. Chung

    (The Hong Kong Polytechnic University)

  • C. K. M. Lee

    (The Hong Kong Polytechnic University)

  • S. S. M. Yuen

    (The Hong Kong Polytechnic University)

Abstract

Pallet loading operations support palletisation and truckload optimisation for e-fulfilment processes. Currently, the pallet loading problem is optimised offline using available cargo information, which is advantageous compared to typical freight operations but results in inefficiency when handling fragmented e-commerce orders. This research develops a mixed reality-based online pallet loading system (MROPLS) supported by deep reinforcement learning technology and online algorithms that dynamically decide cargo placements and orientations without prior information for pallet loading operations. The MROPLS proposes a 3-dimensional maximal-rectangle non-guillotine cutting strategy combined with a deep Q-network to increase space utilisation effectively. This approach is achieved using the lookahead algorithm, which predicts upcoming packages in the online pallet loading process and optimises package spatial location and orientation decision-making. We conduct simulation experiments to verify the system’s feasibility and performance by considering SF Express, DHL and Royal Mail package and ISO pallet sizes. The interaction effects between package types, pallet sizes and lookahead values were found and summarised to determine optimal system settings. With the aid of MROPLS, human intelligence in the online pallet loading process can be augmented, resulting in optimal palletisation in warehouse automation.

Suggested Citation

  • T.T. Yang & Y. P. Tsang & C. H. Wu & K. T. Chung & C. K. M. Lee & S. S. M. Yuen, 2025. "Mixed reality-based online 3D pallet loading problem to achieve augmented intelligence in e-fulfilment processes," Operations Management Research, Springer, vol. 18(2), pages 612-627, June.
    • Handle: RePEc:spr:opmare:v:18:y:2025:i:2:d:10.1007_s12063-023-00432-6
    DOI: 10.1007/s12063-023-00432-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12063-023-00432-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s12063-023-00432-6?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Chen, C. S. & Lee, S. M. & Shen, Q. S., 1995. "An analytical model for the container loading problem," European Journal of Operational Research, Elsevier, vol. 80(1), pages 68-76, January.
    2. Agatz, Niels A.H. & Fleischmann, Moritz & van Nunen, Jo A.E.E., 2008. "E-fulfillment and multi-channel distribution - A review," European Journal of Operational Research, Elsevier, vol. 187(2), pages 339-356, June.
    3. Boysen, Nils & de Koster, René & Weidinger, Felix, 2019. "Warehousing in the e-commerce era: A survey," European Journal of Operational Research, Elsevier, vol. 277(2), pages 396-411.
    4. Kaveh Azadeh & René De Koster & Debjit Roy, 2019. "Robotized and Automated Warehouse Systems: Review and Recent Developments," Transportation Science, INFORMS, vol. 53(4), pages 917-945, July.
    5. Boysen, Nils & de Koster, René & Weidinger, Felix, 2019. "Warehousing in the e-commerce era: A survey," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 126185, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    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. Xuefei Yang & Manuel Ostermeier & Alexander Hübner, 2024. "Winning the race to customers with micro-fulfillment centers: an approach for network planning in quick commerce," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 32(2), pages 295-334, June.
    2. Lamballais, T. & Merschformann, M. & Roy, D. & de Koster, M.B.M. & Azadeh, K. & Suhl, L., 2022. "Dynamic policies for resource reallocation in a robotic mobile fulfillment system with time-varying demand," European Journal of Operational Research, Elsevier, vol. 300(3), pages 937-952.
    3. Boysen, Nils & de Koster, René, 2025. "50 years of warehousing research—An operations research perspective," European Journal of Operational Research, Elsevier, vol. 320(3), pages 449-464.
    4. van der Gaast, Jelmer Pier & Weidinger, Felix, 2022. "A deep learning approach for the selection of an order picking system," European Journal of Operational Research, Elsevier, vol. 302(2), pages 530-543.
    5. Bock, Stefan & Boysen, Nils, 2025. "Stow & pick: Optimizing combined stowing and picking tours in scattered storage warehouses," European Journal of Operational Research, Elsevier, vol. 324(3), pages 1002-1016.
    6. Jiang, Min & Huang, George Q., 2022. "Intralogistics synchronization in robotic forward-reserve warehouses for e-commerce last-mile delivery," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    7. Ma, Benedict Jun & Pan, Shenle & Zou, Bipan & Kuo, Yong-Hong & Huang, George Q., 2025. "Operating policies for robotic cellular warehousing systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 194(C).
    8. Zhuang, Yanling & Zhou, Yun & Yuan, Yufei & Hu, Xiangpei & Hassini, Elkafi, 2022. "Order picking optimization with rack-moving mobile robots and multiple workstations," European Journal of Operational Research, Elsevier, vol. 300(2), pages 527-544.
    9. Jiang, Min & Leung, K.H. & Lyu, Zhongyuan & Huang, George Q., 2020. "Picking-replenishment synchronization for robotic forward-reserve warehouses," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 144(C).
    10. Michele Barbato & Alberto Ceselli & Giovanni Righini, 2024. "A polynomial-time dynamic programming algorithm for an optimal picking problem in automated warehouses," Journal of Scheduling, Springer, vol. 27(4), pages 393-407, August.
    11. Lu Zhen & Jingwen Wu & Haolin Li & Zheyi Tan & Yingying Yuan, 2023. "Scheduling multiple types of equipment in an automated warehouse," Annals of Operations Research, Springer, vol. 322(2), pages 1119-1141, March.
    12. Boysen, Nils & Schwerdfeger, Stefan & W． Ulmer, Marlin, 2023. "Robotized sorting systems: Large-scale scheduling under real-time conditions with limited lookahead," European Journal of Operational Research, Elsevier, vol. 310(2), pages 582-596.
    13. Yang, Jingjing & de Koster, René B.M. & Guo, Xiaolong & Yu, Yugang, 2023. "Scheduling shuttles in deep-lane shuttle-based storage systems," European Journal of Operational Research, Elsevier, vol. 308(2), pages 696-708.
    14. Tutam, Mahmut & De Koster, René, 2024. "To walk or not to walk? Designing intelligent order picking warehouses with collaborative robots," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 190(C).
    15. Žulj, Ivan & Salewski, Hagen & Goeke, Dominik & Schneider, Michael, 2022. "Order batching and batch sequencing in an AMR-assisted picker-to-parts system," European Journal of Operational Research, Elsevier, vol. 298(1), pages 182-201.
    16. Russell Allgor & Tolga Cezik & Daniel Chen, 2023. "Algorithm for Robotic Picking in Amazon Fulfillment Centers Enables Humans and Robots to Work Together Effectively," Interfaces, INFORMS, vol. 53(4), pages 266-282, July.
    17. Maximilian Löffler & Nils Boysen & Michael Schneider, 2022. "Picker Routing in AGV-Assisted Order Picking Systems," INFORMS Journal on Computing, INFORMS, vol. 34(1), pages 440-462, January.
    18. Justkowiak, Jan-Erik & Pesch, Erwin, 2023. "Stronger mixed-integer programming-formulations for order- and rack-sequencing in robotic mobile fulfillment systems," European Journal of Operational Research, Elsevier, vol. 305(3), pages 1063-1078.
    19. Jiang, Zhong-Zhong & Zhao, Jinlong & Sun, Minghe, 2024. "Joint optimization of order picking and delivery in ergonomic picking systems with due dates for sustainability and resilience," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 191(C).
    20. Dirk Briskorn & Nils Boysen & Lennart Zey, 2025. "Scheduling of e-commerce packaging machines: blocking machines and their impact on the performance–waste tradeoff," Journal of Scheduling, Springer, vol. 28(1), pages 101-120, February.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:spr:opmare:v:18:y:2025:i:2:d:10.1007_s12063-023-00432-6. 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: http://www.springer.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.