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Evaluating battery charging and swapping strategies in a robotic mobile fulfillment system

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  • Zou, Bipan
  • Xu, Xianhao
  • Gong, Yeming (Yale)
  • De Koster, René

Abstract

Robotic mobile fulfillment systems (RMFS) have seen many implementations in recent years, due to their high flexibility and low operational cost. Such a system stores goods in movable shelves and uses movable robots to transport the shelves. The robot is battery powered and the battery depletes during operations, which can seriously affect the performance of the system. This study focuses on battery management problem in an RMFS, considering a battery swapping and a battery charging strategy with plug-in or inductive charging. We build a semi-open queueing network (SOQN) to estimate system performance, modeling the battery charging process as a single queue and the battery swapping process as a nested SOQN. We develop a decomposition method to solve the analytical models and validate them through simulation. Our models can be used to optimize battery recovery strategies and compare their cost and throughput time performance. The results show that throughput time performance can be significantly affected by the battery recovery policy, that inductive charging performs best, and that battery swapping outperforms plug-in charging by as large as 4.88%, in terms of retrieval transaction throughput time. However, the annual cost of the RMFS using the battery swapping strategy is generally higher than that of the RMFS using the plug-in charging strategy. In the RMFS that uses the inductive charging strategy, a critical price of a robot can be found, for a lower robot price and a small required retrieval transaction throughput time, inductive charging outperforms both plug-in charging and battery swapping strategies in terms of annual cost. We also find that ignoring the battery recovery will underestimate the number of robots required and the system cost for more than 15%.

Suggested Citation

  • Zou, Bipan & Xu, Xianhao & Gong, Yeming (Yale) & De Koster, René, 2018. "Evaluating battery charging and swapping strategies in a robotic mobile fulfillment system," European Journal of Operational Research, Elsevier, vol. 267(2), pages 733-753.
    • Handle: RePEc:eee:ejores:v:267:y:2018:i:2:p:733-753
    DOI: 10.1016/j.ejor.2017.12.008
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    Cited by:

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    2. 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.
    3. Roy, Debjit & Nigam, Shobhit & de Koster, René & Adan, Ivo & Resing, Jacques, 2019. "Robot-storage zone assignment strategies in mobile fulfillment systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 119-142.
    4. 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.
    5. 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).
    6. Chen, Wanying & Gong, Yeming & Chen, Qi & Wang, Hongwei, 2024. "Does battery management matter? Performance evaluation and operating policies in a self-climbing robotic warehouse," European Journal of Operational Research, Elsevier, vol. 312(1), pages 164-181.
    7. Konrad Lewczuk & Michał Kłodawski & Paweł Gepner, 2021. "Energy Consumption in a Distributional Warehouse: A Practical Case Study for Different Warehouse Technologies," Energies, MDPI, vol. 14(9), pages 1-25, May.
    8. 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).
    9. Mohamed Amjath & Laoucine Kerbache & James MacGregor Smith, 2024. "A Closed Queueing Networks Approach for an Optimal Heterogeneous Fleet Size of an Inter-Facility Bulk Material Transfer System," Logistics, MDPI, vol. 8(1), pages 1-38, March.
    10. 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.
    11. Li, Linman & Li, Yuqing & Liu, Ran & Zhou, Yaoming & Pan, Ershun, 2023. "A Two-stage Stochastic Programming for AGV scheduling with random tasks and battery swapping in automated container terminals," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 174(C).
    12. Srinivas, Sharan & Ramachandiran, Surya & Rajendran, Suchithra, 2022. "Autonomous robot-driven deliveries: A review of recent developments and future directions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 165(C).
    13. Xie, Lin & Thieme, Nils & Krenzler, Ruslan & Li, Hanyi, 2021. "Introducing split orders and optimizing operational policies in robotic mobile fulfillment systems," European Journal of Operational Research, Elsevier, vol. 288(1), pages 80-97.
    14. 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.
    15. 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).
    16. Merschformann, M. & Lamballais, T. & de Koster, M.B.M. & Suhl, L., 2019. "Decision rules for robotic mobile fulfillment systems," Operations Research Perspectives, Elsevier, vol. 6(C).
    17. 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).
    18. Sonja Otten & Ruslan Krenzler & Lin Xie & Hans Daduna & Karsten Kruse, 2022. "Analysis of semi-open queueing networks using lost customers approximation with an application to robotic mobile fulfilment systems," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(2), pages 603-648, June.
    19. 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.
    20. Doo Il Choi & Dae-Eun Lim, 2020. "Analysis of the State-Dependent Queueing Model and Its Application to Battery Swapping and Charging Stations," Sustainability, MDPI, vol. 12(6), pages 1-15, March.
    21. 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.

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