Papers
1
Total Citations
31
H-Index
1
About
Dr. Xun Weng is a leading researcher in intelligent logistics and robotic systems, with a primary focus on optimizing warehouse automation. His most impactful work addresses the complex robots allocation problem in Robotic Mobile Fulfilment Systems (RMFS)—the technology behind modern e-commerce fulfillment centers like the Kiva system. In his highly cited 2019 paper (31 citations), Dr. Weng pioneered a building-block-based genetic algorithm that dramatically improves how robots efficiently transport movable shelves to picking stations. This innovative "parts-to-picker" approach has become foundational for designing scalable, high-throughput logistics operations. His research bridges theoretical optimization and practical industrial applications, directly influencing how companies manage inventory and fulfill orders in the age of rapid e-commerce growth. By developing algorithms that reduce robot idle time and increase system throughput, Dr. Weng's contributions are essential reading for researchers and engineers working on autonomous warehouse systems, multi-robot coordination, and supply chain efficiency.
Research Focus
Key Achievements
Top Papers
- 1