报告题目：Train scheduling optimization with consideration of passenger flows during disturbed operations
报告人简介：Andrea D'Ariano，教授，罗马第三大学(Roma Tre University)土木工程、计算机科学与航空技术工程系。他在罗马第三大学先后获得计算机科学自动化与管理工程的学士和硕士学位。2003年11月，他加入荷兰代尔夫特理工大学(Delft University of Technology)土木工程与地球科学学院的交通与规划系，并成为TRAIL研究学院的成员。2008年4月，在Ingo A. Hansen授的指导下，顺利获得博士学位。D'Ariano教授曾担任欧盟委员会及多个国家研究基金的专家与报告员。他是意大利运筹学协会(AIRO)“公共交通与共享出行优化”分会的协调员，同时担任多个国际知名期刊(如Transportation Research Part B、C、E)的副主编，并积极参与重要学术会议(如IEEE智能交通系统国际会议)的组织工作。他的主要研究方向是调度与路径规划算法的设计与开发，研究成果广泛应用于公共交通和物流领域。
报告内容：Optimization models for railway traffic management tackle the problem of determining, in real-time, control actions to reduce the effect of disturbances. Two main research streams can be identified. On the one hand, train scheduling models are designed to include all conditions relevant to achieve feasible and efficient operation of rail services, keeping as much as possible train punctuality. On the other hand, delay management models focus on the impact of rescheduling decisions on the quality of service perceived by passengers. The resulting objectives are conflicting whenever train delay reduction requires cancellation of some connected services, causing extra waiting times to transferring passengers. The infrastructure manager and the train operating companies need to discuss on which connections to keep or drop.
This talk investigates hybrid railway traffic optimization approaches, merging these two streams of research. First, we consider the bi-objective problem of minimizing train delays and missed connections to provide a set of feasible non-dominated schedules, supporting the decisional process. We use a detailed alternative graph model to ensure schedule feasibility and develop heuristic algorithms to compute the Pareto front of non-dominated schedules. Second, we introduce a comprehensive mathematical model, incorporating the traffic regulations and the passenger rerouting options at a microscopic level. Third, we study this problem as a game theoretical approach, focusing on the solutions corresponding to Nash equilibria of a game involving passengers and infrastructure managers. Computational results based on a conventional Dutch railway network quantify the trade-off between the minimization of train delays and passenger travel times.
