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Storage assignment policy with awareness of energy consumption in the Kiva mobile fulfilment system

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  • Li, Xiaowei
  • Hua, Guowei
  • Huang, Anqiang
  • Sheu, Jiuh-Biing
  • Cheng, T.C.E.
  • Huang, Fengquan

Abstract

To facilitate more efficient and environmentally-friendly order picking operations, this study explores the optimal storage assignment policy in the Kiva mobile fulfilment system. First, temporal association analysis and a clustering approach are employed to identify highly correlated items to be stored in the same rack. Next, in order to avoid AGV blocking, a new turnover-rate-based decentralized storage policy (TRBDSP) is proposed. Subsequently, an order picking performance evaluation method is presented. Finally, simulation studies are performed to ascertain the effectiveness of TRBDSP. The results show that the new approach can significantly improve order picking efficiency and reduce AGV energy consumption.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:transe:v:144:y:2020:i:c:s1366554520308036
    DOI: 10.1016/j.tre.2020.102158
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    7. 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.
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