Multi-Objective Energy-Efficient Train Timetable Optimization in Urban Rail Transit via a Hybrid DRL-NSGA-III Framework
Urban rail transit systems face a pronounced contradiction between escalating traction energy consumption and passenger service quality under the carbon peaking and carbon neutrality goals. This study proposes a hybrid optimization framework offline combining deep reinforcement learning (DRL) and Non-dominated Sorting...
Jixu Zhou, Lijun Zhang, Anping Zheng et al.
· Energies · 0 citations