Planning problems in passenger railway range from long term strategic decision making to
the detailed planning of operations. Operations research methods have played an …

This paper presents an end-to-end deep reinforcement framework to automatically learn a
policy for solving a flexible Job-shop scheduling problem (FJSP) using a graph neural …

Optimization models for railway traffic rescheduling tackle the problem of determining, in real-
time, control actions to reducing the effect of disturbances in railway systems. In this field …

Train dispatching is critical for the punctuality and reliability of rail operations, especially for
a complex rail network. This paper develops an innovative integer programming model for …

In the case of a metro disruption, the planned timetable cannot be operated and a large
number of passengers are left stranded in the stations. When the disruption is over, some …

Rescheduling in railway networks is a challenging problem in both practice and theory. It
requires good quality solutions in reasonable computation time to resolve unexpected …

Focusing on providing a modelling framework for train operation problems, this paper
proposes a new collaborative optimization method for both train stop planning and train …

Unexpected disruptions occur for many reasons in railway networks and cause delays,
cancelations, and, eventually, passenger inconvenience. This research focuses on the …

In this paper we present a stochastic model for predicting the propagation of train delays
based on Bayesian networks. This method can efficiently represent and compute the …

In metro system, the fault of traction power supply system may cause the power supply
shortage around the failure substation. In this case, the dispatching measure should be …