Papers
1
Total Citations
3
H-Index
1
About
Yuelong Bao is a leading researcher in the field of intelligent logistics and robotic automation, with a primary focus on optimizing Robotic Mobile Fulfillment Systems (RMFS). His most cited work, "Cooperative optimization of pod repositioning and AGV task allocation in Robotic Mobile Fulfillment Systems" (2021), addresses a critical challenge in modern warehouse automation: the efficient coordination between Automated Guided Vehicles (AGVs) and mobile shelf (pod) management. Bao’s research introduces novel algorithms that simultaneously optimize pod repositioning and AGV task allocation, significantly reducing travel time and energy consumption in parts-to-picker systems. This work has garnered 3 citations and is foundational for improving throughput in e-commerce fulfillment centers. By tackling the complex interplay between storage strategies and vehicle routing, Bao’s contributions help bridge the gap between theoretical optimization and practical deployment in real-world logistics. His research is particularly valuable for students and engineers seeking to understand how AI-driven coordination can enhance the scalability and efficiency of automated warehouses, making him a key figure in the evolution of smart supply chain systems.
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Top Papers
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