IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i5p1742-d1342418.html
   My bibliography  Save this article

Storage Location Assignment for Improving Human–Robot Collaborative Order-Picking Efficiency in Robotic Mobile Fulfillment Systems

Author

Listed:
  • Yue Chen

    (School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China)

  • Yisong Li

    (School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China)

Abstract

The robotic mobile fulfillment (RMF) system is a parts-to-picker warehousing system and a sustainable technology used in human–robot collaborative order picking. Storage location assignment (SLA) tactically benefits order-picking efficiency. Most studies focus on the retrieval efficiency of robots to solve SLA problems. To further consider the crucial role played by human pickers in RMF systems, especially in the context that the sustainable performance of human workers should be paid attention to in human–robot collaboration, we solve the SLA problem by aiming to improve human–robot collaborative order-picking efficiency. This study specifically makes decisions on assigning multiple items of various products to the slots of pods in the RMF system, in which human behavioral factors are taken into account. To obtain the solution in one mathematical model, we propose the heuristic algorithm under a two-stage optimization method. The results show that assigning correlated products to pods improves the retrieval efficiency of robots compared to class-based assignment. We also find that assigning items of each product to slots of pods, considering behavioral factors, benefits the operation efficiency of human pickers compared to random assignment. Improving human–robot collaborative order-picking efficiency and increasing the capacity usage of pods benefits sustainable warehousing management.

Suggested Citation

  • Yue Chen & Yisong Li, 2024. "Storage Location Assignment for Improving Human–Robot Collaborative Order-Picking Efficiency in Robotic Mobile Fulfillment Systems," Sustainability, MDPI, vol. 16(5), pages 1-25, February.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:5:p:1742-:d:1342418
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/5/1742/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/16/5/1742/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ang, Marcus & Lim, Yun Fong, 2019. "How to optimize storage classes in a unit-load warehouse," European Journal of Operational Research, Elsevier, vol. 278(1), pages 186-201.
    2. Catherine Marinagi & Panagiotis Reklitis & Panagiotis Trivellas & Damianos Sakas, 2023. "The Impact of Industry 4.0 Technologies on Key Performance Indicators for a Resilient Supply Chain 4.0," Sustainability, MDPI, vol. 15(6), pages 1-31, March.
    3. Bartolini, M. & Bottani, E. & Grosse, E. H., 2019. "Green warehousing: systematic literature review and bibliometric analysis," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 112369, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    4. de Koster, Rene & Le-Duc, Tho & Roodbergen, Kees Jan, 2007. "Design and control of warehouse order picking: A literature review," European Journal of Operational Research, Elsevier, vol. 182(2), pages 481-501, October.
    5. Boysen, Nils & de Koster, René & Füßler, David, 2021. "The forgotten sons: Warehousing systems for brick-and-mortar retail chains," European Journal of Operational Research, Elsevier, vol. 288(2), pages 361-381.
    6. Roodbergen, Kees Jan & Vis, Iris F.A., 2009. "A survey of literature on automated storage and retrieval systems," European Journal of Operational Research, Elsevier, vol. 194(2), pages 343-362, April.
    7. Syaiful Anwar Mohamed & Moamin A. Mahmoud & Mohammed Najah Mahdi & Salama A. Mostafa, 2022. "Improving Efficiency and Effectiveness of Robotic Process Automation in Human Resource Management," Sustainability, MDPI, vol. 14(7), pages 1-18, March.
    8. Sgarbossa, F. & Grosse, E. H. & Neumann, W. P. & Battini, D. & Glock, C. H., 2020. "Human factors in production and logistics systems of the future," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 120615, 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. Polten, Lukas & Emde, Simon, 2022. "Multi-shuttle crane scheduling in automated storage and retrieval systems," European Journal of Operational Research, Elsevier, vol. 302(3), pages 892-908.
    2. Li, Xiaowei & Hua, Guowei & Huang, Anqiang & Sheu, Jiuh-Biing & Cheng, T.C.E. & Huang, Fengquan, 2020. "Storage assignment policy with awareness of energy consumption in the Kiva mobile fulfilment system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 144(C).
    3. Hyun-woo Jeon & Ahmad Ebrahimi & Ga-hyun Lee, 2023. "A Simulation-Based Experimental Design for Analyzing Energy Consumption and Order Tardiness in Warehousing Systems," Sustainability, MDPI, vol. 15(20), pages 1-25, October.
    4. Mohammed Alnahhal & Bashir Salah & Rafiq Ahmad, 2022. "Increasing Throughput in Warehouses: The Effect of Storage Reallocation and the Location of Input/Output Station," Sustainability, MDPI, vol. 14(8), pages 1-16, April.
    5. Bortolini, Marco & Faccio, Maurizio & Ferrari, Emilio & Gamberi, Mauro & Pilati, Francesco, 2017. "Time and energy optimal unit-load assignment for automatic S/R warehouses," International Journal of Production Economics, Elsevier, vol. 190(C), pages 133-145.
    6. Chen, Ran & Yang, Jingjing & Yu, Yugang & Guo, Xiaolong, 2023. "Retrieval request scheduling in a shuttle-based storage and retrieval system with two lifts," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 174(C).
    7. Nicolas, Lenoble & Yannick, Frein & Ramzi, Hammami, 2018. "Order batching in an automated warehouse with several vertical lift modules: Optimization and experiments with real data," European Journal of Operational Research, Elsevier, vol. 267(3), pages 958-976.
    8. Zhuang, Yanling & Zhou, Yun & Hassini, Elkafi & Yuan, Yufei & Hu, Xiangpei, 2024. "Improving order picking efficiency through storage assignment optimization in robotic mobile fulfillment systems," European Journal of Operational Research, Elsevier, vol. 316(2), pages 718-732.
    9. Azadeh, K. & de Koster, M.B.M. & Roy, D., 2017. "Robotized Warehouse Systems: Developments and Research Opportunities," ERIM Report Series Research in Management ERS-2017-009-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.
    10. Atashi Khoei, Arsham & Süral, Haldun & Tural, Mustafa Kemal, 2023. "Energy minimizing order picker forklift routing problem," European Journal of Operational Research, Elsevier, vol. 307(2), pages 604-626.
    11. Claeys, Dieter & Adan, Ivo & Boxma, Onno, 2016. "Stochastic bounds for order flow times in parts-to-picker warehouses with remotely located order-picking workstations," European Journal of Operational Research, Elsevier, vol. 254(3), pages 895-906.
    12. Marcus Ang & Yun Fong Lim & Melvyn Sim, 2012. "Robust Storage Assignment in Unit-Load Warehouses," Management Science, INFORMS, vol. 58(11), pages 2114-2130, November.
    13. Nils Boysen & David Füßler & Konrad Stephan, 2020. "See the light: Optimization of put‐to‐light order picking systems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 67(1), pages 3-20, February.
    14. Yu, Y. & de Koster, M.B.M., 2009. "On the Suboptimality of Full Turnover-Based Storage," ERIM Report Series Research in Management ERS-2009-051-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.
    15. 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.
    16. Loske, Dominic & Klumpp, Matthias & Grosse, Eric H. & Modica, Tiziana & Glock, Christoph H., 2023. "Storage systems’ impact on order picking time: An empirical economic analysis of flow-rack storage systems," International Journal of Production Economics, Elsevier, vol. 261(C).
    17. Diefenbach, Heiko & Grosse, Eric H. & Glock, Christoph H., 2024. "Human-and-cost-centric storage assignment optimization in picker-to-parts warehouses," European Journal of Operational Research, Elsevier, vol. 315(3), pages 1049-1068.
    18. Boysen, Nils & Schwerdfeger, Stefan & Stephan, Konrad, 2023. "A review of synchronization problems in parts-to-picker warehouses," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1374-1390.
    19. Shandong Mou, 2022. "Integrated Order Picking and Multi-Skilled Picker Scheduling in Omni-Channel Retail Stores," Mathematics, MDPI, vol. 10(9), pages 1-19, April.
    20. Jianming Cai & Xiaokang Li & Yue Liang & Shan Ouyang, 2021. "Collaborative Optimization of Storage Location Assignment and Path Planning in Robotic Mobile Fulfillment Systems," Sustainability, MDPI, vol. 13(10), pages 1-26, May.

    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:gam:jsusta:v:16:y:2024:i:5:p:1742-:d:1342418. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.