Buqing Jie

Xi'an Technological University

Papers

1

Total Citations

2

H-Index

1

About

Buqing Jie is a researcher focused on intelligent logistics and industrial automation, with a particular emphasis on optimizing material handling systems in manufacturing environments. Their most notable contribution is the development of an improved genetic algorithm for scheduling multi-load Automated Guided Vehicles (AGVs), addressing critical inefficiencies in factories producing large parts. This work, published in 2023, tackles the heavy workload and prolonged handling times associated with manual forklift operations by introducing intelligent AGVs for streamlined factory logistics. While still early in its citation impact, this research represents a practical advancement in smart manufacturing, offering a scalable solution for real-world industrial challenges. Jie’s work bridges algorithmic optimization and applied robotics, contributing to the growing field of Industry 4.0. Their research underscores the potential of computational methods to transform traditional material transport, reducing human labor and enhancing operational efficiency. As automated logistics becomes increasingly vital in modern production systems, Jie’s contributions provide a foundation for further innovation in AGV scheduling and intelligent factory design.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
Research on Multi-load AGV Scheduling Based on Improved Genetic Algorithm
2 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: Xi'an Technological University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago