The conflict between train timetable and maintenance skylight was inevitable,and the duration of maintenance skylight significantly impacts train operation time.To address this,a dual-objective mixed integer programming model was proposed.It could minimize the total train operation time and the overall deviation between the actual and ideal durations of maintenance skylight while considering various constraints such as speed restrictions imposed by maintenance skylight and the number of arrival-departure lines.Intermediate auxiliary variables were introduced to improve solution efficiency.A constraint transformation algorithm was designed to obtain the Pareto optimality for the model.The railway line was micro-managed by refining station resources and inter-station resources into a series of train resource units,aiming to obtain a more suitable timetable with transportation needs.Under the background of nighttime train operations and maintenance skylight scheduling on a specific railway line,a commercial software was employed to obtain the Pareto optimality.Comparative analysis was performed between minimum and optimal dominant solutions.Based on the optimal dominant solutions,the timetable was depicted,considering train arrivals and departures,station dwell times,and maintenance skylight schedules.The results can demonstrate satisfied constraints,minimize operation time,and increase maintenance skylight duration.The generated timetable aligns better with actual passenger transportation needs.These findings can provide valuable insights for optimizing train timetable compilation and maintenance skylight scheduling in railway operations and management.
关键词
铁路运输/列车运行图/维修天窗/到发线数量/约束转换算法/Pareto最优
Key words
railway transportation/train timetable/maintenance skylight/the number of arrival-departure lines/constraint transformation algorithm/Pareto optimality
维普
万方数据