Huiwen Bai
Papers
1
Total Citations
9
H-Index
1
About
Huiwen Bai is a leading researcher in the optimization of autonomous mobile robot (AMR) systems for modern warehousing and logistics. Her work focuses on the critical intersection of order sequencing, tote scheduling, and robot routing, particularly within multi-tote storage and retrieval systems. In her highly cited 2024 study, Bai tackles the complex joint optimization problem of coordinating these three interdependent operations in a single, integrated framework. This research is foundational for improving efficiency in e-commerce and distribution centers, where AMRs must transport multiple SKU bins simultaneously. By developing novel algorithms that minimize travel time and maximize throughput, Bai’s contributions directly enhance the scalability and cost-effectiveness of automated fulfillment. With her work already garnering early citations, she is establishing herself as a key voice in the next generation of logistics automation, bridging the gap between theoretical optimization and practical, real-world warehouse operations.
Research Focus
Key Achievements
Top Papers
- 1