Papers
Logistics & Transportation Networks
Deep Reinforcement Learning Enhances Demand-Driven Services in Logistics and Transportation
The paper "Deep Reinforcement Learning for Demand Driven Services in Logistics and Transportation Systems: A Survey" by Zefang Zong, Jingwei Wang, et al. explores the application of deep reinforcement learning (DRL) to improve demand-driven services (DDS) such as on-demand delivery, ridesharing, express systems, and warehousing. The authors highlight the challenges in managing these services and how DRL can provide more flexible and efficient solutions compared to traditional methods.