This paper presents an overview of recovery models and algorithms for real-time railway
disturbance and disruption management. This area is currently an active research area in …

Benders decomposition uses a strategy of``learning from one's mistakes.''The aim of this
paper is to extend this strategy to a much larger class of problems. The key is to generalize …

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 …

This paper studies the problem of rescheduling trains in a large-scale railway network with
the characteristics of long distance, long time horizon and a large number of trains, where a …

For high-frequency metro lines, the excessive travel demand during the peak hours brings a
high risk to metro system and a low comfort to passengers, so it is important to consider …

This paper deals with the real-time problem of scheduling and routing trains in a railway
network. In the related literature, this problem is usually solved starting from a subset of …

Railway operations are vulnerable to unexpected disruptions that should be handled in an
efficient and passenger-friendly way. To this end, we propose a timetable rescheduling …

Train rescheduling problems have received significant attention in the operations research
community during the past 20–30 years. These are complex problems with many aspects …

Trains normally run as scheduled in a non-disrupted situation. However, due to external
and/or internal factors, trains may deviate from their original timetable during daily …

This paper addresses the problem of improving the integration between passenger
timetabling and track maintenance scheduling. We propose a microscopic optimization …