|17-运输与物流讲堂-Multi-objective periodic railway timetabling|
延斐，荷兰代尔夫特理工大学运输与规划系，本科、研究生均毕业于北京交通大学交通运输学院。目前其主要研究方向为铁路列车开行方案优化、列车时刻表优化、铁路客流预测、客流分配、时刻表鲁棒性分析、运输路网能力分析和铁路基础设施选址优化。2016年参与荷兰铁路公司项目SmartOCCR，负责铁路网络故障中断过程中多种预测故障时间长度下的旅客路径选择及分析反馈。2018年参加美国运筹学与管理科学协会INFORMS RAS Competition获得论文竞赛第一名。
The rail system becomes more and more complex, and different performance indicators need to be taken into account during the timetabling process. Accordingly, the single-objective optimization models become difficult to find high-quality timetables considering multiple indicators. Therefore, this presentation proposed a new multi-objective periodic railway timetabling (MOPRT) model and solution approach with four objectives to be minimized: train journey time, timetable regularity deviation, timetable vulnerability and the number of overtakings. The aim is to find an efficient, regular and robust timetable that utilizes the infrastructure capacity as good as possible. Based on the Periodic Event Scheduling Problem, MOPRT problem is formulated as a Mixed Integer Linear Program (MILP). The ε-constraint method is applied to deal with the multi-objective property, and algorithms are designed to efficiently create the Pareto frontier. By solving the problem for different values of ε, the four-dimensional Pareto frontier is explored to uncover the trade-offs among the four objectives and the optimal solution is obtained by using standardized Euclidean distance. Computational experiments are performed on a theoretical instance and a real instance in one direction of a Dutch railway corridor, demonstrating the efficiency of the model and approach.