国家高速列车技术创新中心研发项目:“新型高效能城市轨道交通系统建模与综合智能优化”(批准号Grant No. CX/KJ-2020- 0006)
1.Tsinghua University;2.National Innovation Center of High Speed Train
National Innovation Center of High Speed Train R&D project: “Modeling and comprehensive intelligent optimization for new high efficiency urban rail transit system” (Grant No. CX/KJ-2020- 0006)
Optimizing timetable is an important method to enhance energy efficiency and passenger experience in urban rail transit systems. Tidal passenger flow brings difficulties to the optimization of timetable.In the meantime, train quantity restriction is necessary but got little attention in previous studies. To solve these problems, a nonlinear multi-objective optimizing problem considering train quantity restriction is proposed in this paper. The decision variables are train headway at the origin station. Two optimization objectives,which are train energy efficiency and passenger experience, are designed based on train operation model and passenger behavior model. NSGA-II algorithm is used to solve this multi-objective problem. One case study is conducted to evaluate the performance of timetable given train quantity based on the real data. The results show that by relaxing the limit on the train quantity, the energy efficiency can be improved by up to 11.1%, and that by designing an asymmetric timetable, the train efficiency can be improved by up to 4.6%.When the passenger flow has tidal characteristics, significant benefits can be achieved by designing asymmetric timetable.