Papers

1

Total Citations

17

H-Index

1

About

Dr. Teng Ying is a distinguished researcher in industrial engineering and operations research, with a primary focus on advanced manufacturing scheduling and optimization. Her key research areas include metaheuristic algorithms, multi-objective optimization, and robotic cell scheduling—critical domains for enhancing productivity in smart manufacturing systems. Dr. Ying’s most notable contribution is her work on the multi-objective job shop scheduling problem in a robotic cell (MOJRCSP), where she developed innovative metaheuristic approaches to simultaneously optimize makespan, energy consumption, and machine utilization. Her 2020 paper on this topic has garnered 17 citations, establishing a foundation for subsequent studies in automated production environments. By addressing the unique challenge of job transportation handled by robots—a departure from classical job shop models—Dr. Ying’s research bridges the gap between theoretical scheduling and real-world robotic manufacturing. Her work is particularly impactful for industries adopting Industry 4.0 principles, where efficient coordination between machines and robots is paramount. Dr. Ying continues to advance the field through her rigorous algorithmic designs, offering practical solutions for complex, multi-objective scheduling problems in modern factories.

Research Focus

Key Achievements

1
H-Index
1
Papers
17
Total Citations
17
Avg Citations/Paper
🏆 Most Cited Paper
Metaheuristic for Solving Multi-Objective Job Shop Scheduling Problem in a Robotic Cell
17 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: University of Electronic Science and Technology of China

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago