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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
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    References listed on IDEAS

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    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. 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.
    3. 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.
    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. 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).
    6. 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).
    7. 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.
    8. 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.
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