考虑节能与延误恢复的轨道交通列车运行标尺协同优化OA

As the core parameters for developing urban rail transit timetables,the rational configuration of train running time standards is crucial for enhancing operational stability and reducing energy consumption.To address the limited practical benefits of energy-saving optimization schemes under train operation deviations,this study proposed a configuration method for train running time standards that integrates energy efficiency and delay recovery.The aim was to achieve energy-saving optimization while maintaining delay control,thereby improving the practicality of energy-saving schemes.First,a Gaussian passenger flow model was employed to characterize the uncertainty of station-level passenger demand,and a delay propagation recursive model was developed to quantify the absorption effect of buffer time on delays.Subsequently,with the objective of minimizing the combined impact of expected delays and expected traction energy consumption,a stochastic optimization model for train running time standards was constructed from a single-trip perspective.Monte Carlo simulations were utilized to generate random passenger flow scenarios,and a genetic algorithm incorporating a Lagrangian relaxation strategy was designed for solution.A case study demonstrated that the proposed method significantly reduced station delay levels during peak hours and achieved an approximately 7.8%reduction in single-trip traction energy consumption.During off-peak hours,it attains greater energy savings while ensuring zero delays.The method adapted the configuration strategy of running time standards according to different passenger flow patterns(peak/off-peak),thereby enhancing the implementability and adaptability of the scheme.By fine-tuning inter-station running times and dwell times,it effectively improves the implementation stability of the energy-saving scheme,providing robust decision support for developing highly reliable and energy-efficient urban rail transit timetables.