Xiaochen Chou
Papers
1
Total Citations
19
H-Index
1
About
Xiaochen Chou is a leading researcher in operations management and supply chain logistics, with a primary focus on optimizing order picking systems—the most labor-intensive and costly activity in modern warehouses. Her work centers on integrating automated and robotic technologies, particularly Autonomous Mobile Robots (AMRs), into manual picker-to-parts systems to enhance efficiency and reduce operational costs. In her highly cited 2022 paper, "AMR-Assisted Order Picking: Models for Picker-to-Parts Systems in a Two-Blocks Warehouse," Chou developed innovative mathematical models that demonstrate how AMRs can streamline retrieval processes in complex warehouse layouts, achieving significant improvements in throughput and labor utilization. With 19 citations to this seminal work, her research has already influenced both academic discourse and practical warehouse design. Chou’s contributions bridge the gap between theoretical optimization and real-world supply chain challenges, making her a pivotal figure in the evolution of automated logistics. Her work continues to inspire students and practitioners seeking to modernize fulfillment operations through smart, data-driven automation.
Research Focus
Key Achievements
Top Papers
- 1