Joint order assignment and picking station scheduling in KIVA warehouses with multiple stations
Yang, Xiying, Hua, Guowei, Zhang, Li, Cheng, T. C. E, Choi, Tsan Ming
–arXiv.org Artificial Intelligence
The rapid development of e-commerce has brought new challenges to warehouse operations. Order picking plays a crucial role among all these operations, which directly affects the overall order fulfillment efficiency (Lamballais et al., 2017; Shen et al., 2020). The Robotic Mobile Fulfillment System (RMFS) is invented to improve order picking efficiency and reduce labour costs by exploiting rack-moving mobile robots (Boysen et al., 2017). The cooperation between the robots and movable racks eliminates pickers' unproductive movement in the picker-to-parts system (Battini et al., 2017). Compared with traditional manual warehouses, the picking performance of RMFS is far superior, which is reported to achieve over 600 order-lines per hour per workstation (Wulfraat, 2012; Banker, 2016). Nevertheless, order picking in RMFS needs further efficiency improvement due to the growing demand and increasingly tight delivery schedules brought by the prosperity of e-commerce (Batt & Gallino, 2019; Azadeh et al., 2017; Zhuang et al., 2021).
arXiv.org Artificial Intelligence
May-5-2023
- Country:
- Asia
- Europe > United Kingdom (0.04)
- North America > United States
- California > San Francisco County > San Francisco (0.04)
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- Research Report (1.00)
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- Information Technology (0.54)
- Transportation > Freight & Logistics Services (0.46)
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