理工学研究科博士後期課程に在学中の陳 錦華 (CHEN Jinhua)さん（IIST生）が、IEEE VTC2024-SpringでYoung Researcher's Encouragement Awardを受賞しました。
・受賞者
陳 錦華 (CHEN Jinhua) （理工学研究科応用情報工学専攻博士後期課程1年、IIST生）
・学会名
IEEE VTC2024-Spring
・受賞日
2024年6月25日
・受賞名
Young Researcher's Encouragement Award
・受賞論文名
Enhancing Production Planning in the Internet of Vehicles: A Transformer-based Federated Reinforcement Learning Approach
・共著者
Zihan Zhao (Hosei University), Keping Yu(Hosei University), Shahid Mumtaz (Nottingham Trent University, UK), Joel J. P. C. Rodrigues (Lusofona University, Portugal), Mohsen Guizani (Mohamed Bin Zayed University of Artificial Intelligence, UAE), Takuro Sato (Waseda University, Japan)
・研究内容の概要
The Internet of Vehicles (IoV) brings significant economic benefits to countries. However, large-scale smart vehicle production planning remains challenging in the IoV. Currently,heuristic algorithms and solvers commonly used for these problems often lack scalability and fall into local optima. Moreover, security concerns about wireless data transfer arising from multi-factory manufacturing processes are garnering attention. To address these issues, this paper introduces an algorithm, TRL, which is a Transformer-based Reinforcement Learning for vehicle production planning problems. Furthermore, we propose a Transformer-based Federated Reinforcement Learning algorithm, named TFRL, tailored for large-scale manufacturing and secure wireless communication. Experimental results showcase the high performance and security of TFRL. It schedules 1000 orders in about 14 seconds and avoids exchanging plaintext during interaction. Compared to NSGA-II, the TFRL enhances computational speed by 95.11% and reduces constraint violation scores by 93.18%.
