ptimization 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.

CALPHAD方法在铝合金、镁合金及钢铁材料中的应用

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