Wenfeng Zhou
Papers
1
Total Citations
17
H-Index
1
About
Wenfeng Zhou is a leading researcher in intelligent transportation systems and logistics optimization, with a particular focus on automated container terminals. His work centers on applying multi-agent reinforcement learning to solve complex real-time control problems in port operations. Zhou’s most-cited paper, "A multi-agent reinforcement learning approach for ART adaptive control in automated container terminals" (2024), has already garnered 17 citations, reflecting its timely impact on the field. In this study, he pioneered a decentralized learning framework that enables automated guided vehicles to dynamically adapt their scheduling and routing decisions, significantly improving terminal throughput and energy efficiency. This contribution addresses a critical bottleneck in smart port logistics, offering scalable solutions for next-generation maritime supply chains. Zhou’s research is notable for bridging theoretical reinforcement learning advances with practical industrial applications, earning recognition from both academic and engineering communities. His work continues to influence the development of autonomous systems in logistics, making him a key voice in the evolution of intelligent container terminals.
Research Focus
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Top Papers
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