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Inventory allocation in robotic mobile fulfillment systems

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Listed:
  • Tim Lamballais Tessensohn
  • Debjit Roy
  • René B.M. De Koster

Abstract

A Robotic Mobile Fulfillment System is a recently developed automated, parts-to-picker material handling system. Robots can move storage shelves, also known as inventory pods, between the storage area and the workstations and can continually reposition them during operations. This article shows how to optimize three key decision variables: (i) the number of pods per SKU; (ii) the ratio of the number of pick stations to replenishment stations; and (iii) the replenishment level per pod. Our results show that throughput performance improves substantially when inventory is spread across multiple pods, when an optimum ratio between the number of pick stations to replenishment stations is achieved and when a pod is replenished before it is completely empty. This article contributes methodologically by introducing a new type of Semi-Open Queueing Network (SOQN): cross-class matching multi-class SOQN, by deriving necessary stability conditions, and by introducing a novel interpretation of the classes.

Suggested Citation

  • Tim Lamballais Tessensohn & Debjit Roy & René B.M. De Koster, 2020. "Inventory allocation in robotic mobile fulfillment systems," IISE Transactions, Taylor & Francis Journals, vol. 52(1), pages 1-17, January.
    • Handle: RePEc:taf:uiiexx:v:52:y:2020:i:1:p:1-17
    DOI: 10.1080/24725854.2018.1560517
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    Citations

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    Cited by:

    1. 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.
    2. 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.
    3. Mirzaei, Masoud & Zaerpour, Nima & de Koster, René, 2021. "The impact of integrated cluster-based storage allocation on parts-to-picker warehouse performance," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 146(C).
    4. Gharehgozli, Amir & Zaerpour, Nima, 2020. "Robot scheduling for pod retrieval in a robotic mobile fulfillment system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    5. 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.
    6. Fragapane, Giuseppe & de Koster, René & Sgarbossa, Fabio & Strandhagen, Jan Ola, 2021. "Planning and control of autonomous mobile robots for intralogistics: Literature review and research agenda," European Journal of Operational Research, Elsevier, vol. 294(2), pages 405-426.
    7. Amjath, Mohamed & Kerbache, Laoucine & Smith, James MacGregor & Elomri, Adel, 2022. "Fleet sizing of trucks for an inter-facility material handling system using closed queueing networks," Operations Research Perspectives, Elsevier, vol. 9(C).
    8. Xu, Xianhao & Chen, Yuerong & Zou, Bipan & Gong, Yeming, 2022. "Assignment of parcels to loading stations in robotic sorting systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    9. Zhuang, Yanling & Zhou, Yun & Hassini, Elkafi & Yuan, Yufei & Hu, Xiangpei, 2022. "Rack retrieval and repositioning optimization problem in robotic mobile fulfillment systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 167(C).

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