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Joint optimization of order picking and replenishment in robotic mobile fulfillment systems

Author

Listed:
  • Wu, Jingwen
  • Yang, Zhiyuan
  • Zhen, Lu
  • Li, Wenxin
  • Ren, Yiran

Abstract

Advancements in intelligent warehousing have spotlighted the robotic mobile fulfillment system as a transformative solution for modern logistics challenges. This paper introduces a five-stage mixed-integer programming model designed to optimize the robotic mobile fulfillment system (RMFS) by minimizing the longest completion time, a critical metric in warehouse efficiency. Our comprehensive model strategically integrates the assignment of orders to stations and pods, the deployment of pods to robots, and the intricate details of route planning, order picking, and replenishment. Utilizing a variable neighborhood search algorithm, we not only tackle the complex scheduling decisions among orders, robots, stations, and pods but also demonstrate the model’s effectiveness through rigorous numerical experiments. The results provide pivotal insights, revealing significant potential for enhancing the RMFS efficiency and offering practical guidance for warehouse managers.

Suggested Citation

  • Wu, Jingwen & Yang, Zhiyuan & Zhen, Lu & Li, Wenxin & Ren, Yiran, 2025. "Joint optimization of order picking and replenishment in robotic mobile fulfillment systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 194(C).
    • Handle: RePEc:eee:transe:v:194:y:2025:i:c:s1366554524005210
    DOI: 10.1016/j.tre.2024.103930
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