Shan Ouyang
Papers
1
Total Citations
40
H-Index
1
About
Shan Ouyang is a leading researcher in intelligent logistics and green warehousing systems, with a focus on optimizing robotic mobile fulfillment systems (RMFS) for sustainable supply chain operations. Her seminal work, "Collaborative Optimization of Storage Location Assignment and Path Planning in Robotic Mobile Fulfillment Systems" (2021, 40+ citations), pioneers an integrated approach that simultaneously addresses two critical challenges in automated warehousing: where to store inventory and how robots should navigate to retrieve it. By demonstrating that joint optimization of these interconnected problems yields superior efficiency over traditional sequential methods, Ouyang has provided foundational insights for next-generation e-commerce fulfillment centers. Her research directly contributes to reducing energy consumption and operational waste in logistics, aligning with global green technology initiatives. Ouyang’s contributions are particularly notable for bridging theoretical optimization models with practical implementation in real-world robotic systems, making her work highly cited among both academics and industry practitioners. As automated warehousing continues to expand, Ouyang’s collaborative optimization framework remains a cornerstone reference for researchers and engineers seeking to design more intelligent, sustainable, and cost-effective fulfillment operations.
Research Focus
Key Achievements
Top Papers
- 1