Yubin is a Ph.D. student at the Transport Systems & Logistics Laboratory (TSL) under the supervision of Dr. Panagiotis Angeloudis. His research focuses on the application of autonomous technologies in urban freight transportation based on evolutionary algorithms, reinforcement learning, and multi-agent modelling. His research interests lie in the intersection of transportation science and supply chain management, and more specifically in multi-agent control and freight transport modelling of logistics operations.
Yubin holds a Bachelor's Degree in Logistics Engineering, having been awarded a China National Scholarship and recognised as a Merit student of the province in 2016 and 2017, and awarded outstanding undergraduate student in 2018. This was followed by an MSc in Logistics and Supply Chain Management from Cranfield Unversity, graduating with distinction honours. He has previously carried out research in the physical network design for cold chain logistics, path planning for logistics robots, and route optimisation for delivery fleets.
Yubin received the Best Research Paper Award of Urban Freight Transportation Committee at the 102nd US Transportation Research Board Annual Meeting for his work on the efficient use of autonomous vehicle fleets for urban freight distribution.
et al., 2023, Route planning for last-mile deliveries using mobile parcel lockers: a hybrid q-learning network approach, Transportation Research Part E: Logistics and Transportation Review, Vol:177, ISSN:1366-5545, Pages:1-40