Papers
3
Total Citations
23
H-Index
3
About
Guoshuai Jiao is a researcher specializing in intelligent logistics, robotics-driven automation, and combinatorial optimization, with a particular focus on revolutionizing warehouse and fulfillment operations through algorithmic innovation. His most influential work addresses the Container Loading Problem based on Robotic Loader Systems (CLP-RLS), published in 2023 and accumulating 17 citations, which tackles the emerging challenge of replacing human labor with robots in cargo loading — a problem requiring entirely new packing pattern frameworks distinct from traditional approaches. Jiao has also made meaningful contributions to Robotic Mobile Fulfillment Systems (RMFS), investigating how Automated Guided Vehicles (AGVs) can be optimally coordinated for pod repositioning, task allocation, and order picking processes. His 2021 work on cooperative AGV optimization and his 2025 study on online joint order picking reflect a sustained commitment to solving real-time, multi-agent decision-making problems in smart warehouses. With research spanning foundational system design to dynamic operational scheduling, Jiao's work sits at the critical intersection of operations research and intelligent manufacturing, making it highly relevant for students and practitioners navigating the rapidly evolving landscape of automated logistics.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3