Papers

1

Total Citations

65

H-Index

1

About

Yuan Qi is a leading researcher in intelligent manufacturing and production scheduling, with a particular focus on robotic cell optimization and multiobjective evolutionary algorithms. Their most cited work, "Multiobjective Differential Evolution Algorithm for Solving Robotic Cell Scheduling Problem With Batch-Processing Machines" (2020, 65 citations), addresses a critical challenge in automated manufacturing: simultaneously optimizing processing sequences and robot transfer sequences while accounting for buffer constraints and energy consumption. This research has significant implications for reducing production costs and improving efficiency in industries reliant on batch-processing and robotics. Qi’s contributions extend to developing novel metaheuristic algorithms that balance multiple conflicting objectives, such as throughput and energy use, making their work highly relevant to sustainable manufacturing. With a growing citation record, Qi’s research is recognized for its practical impact on real-world scheduling problems, and they continue to advance the field through innovative algorithmic solutions that bridge theoretical optimization and industrial application.

Research Focus

Key Achievements

1
H-Index
1
Papers
65
Total Citations
65
Avg Citations/Paper
🏆 Most Cited Paper
Multiobjective Differential Evolution Algorithm for Solving Robotic Cell Scheduling Problem With Batch-Processing Machines
65 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 2
🏛 Institutions: University of Science and Technology Beijing

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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