About

Pengyu Yan is a leading researcher in the optimization of automated manufacturing and logistics systems, with a primary focus on robotic cell scheduling and material handling. His work bridges the gap between theoretical combinatorial optimization and practical industrial applications, particularly in environments with time window constraints and dynamic disturbances. Yan’s most influential contributions include the development of exact and metaheuristic algorithms—such as branch and bound, tabu search, and hybrid artificial immune systems—for cyclic scheduling problems that maximize throughput while respecting processing time windows. His research has garnered over 280 citations, with his 2009 paper on branch and bound for optimal cyclic scheduling receiving 49 citations and his 2018 dynamic scheduling approach accumulating 47. More recently, Yan has extended his expertise to e-grocery delivery networks, pioneering work on Physical Internet-enabled systems and two-echelon vehicle routing problems with mixed vehicle fleets. His 2021 paper on hybrid artificial immune algorithms for Van-Robot delivery systems has already attracted 41 citations, underscoring the timeliness and impact of his logistics research. Yan’s work is essential reading for anyone interested in the intersection of operations research, robotics, and smart logistics.

Research Focus

Key Achievements

7
H-Index
12
Papers
290
Total Citations
24
Avg Citations/Paper
🏆 Most Cited Paper
A branch and bound algorithm for optimal cyclic scheduling in a robotic cell with processing time windows
49 citations · 2009
📈 Most Prolific Year: 2009 (2 Papers)
🤝 Key Collaborators: 19
🏛 Institutions: Université de Technologie de Troyes, University of Electronic Science and Technology of China, Northwestern Polytechnical University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago