Statistical modelling of delays in a rail freight transportation network

Abstract

This study analyzes the transportation network of a major rail freight operator in order to obtain a model of delay propagation of trains connecting intermodal terminals. Operational management of a rail freight operator needs to take into account deviations due to unexpected events such as unplanned maintenance, strikes, railroad works, traffic congestion. The dispatcher makes train assignment decisions based on a number of performance indicators and also on the expectancy that a given train, currently delayed, could recover or limit the amount of delay in the future. We have developed a Markov-chain based model in order to evaluate the evolution of train delays as a train visits successive terminals. Our model is based on the examination of a large set of historical data and we show how we can classify different terminals according to their ability either to absorb or to amplify delays.

Original document

The different versions of the original document can be found in:

• http://www.informs-sim.org/wsc12papers/includes/files/inv111.pdf

• http://xplorestaging.ieee.org/ielx7/6451330/6464965/06465188.pdf?arnumber=6465188,

http://dx.doi.org/10.1109/wsc.2012.6465188

• https://ieeexplore.ieee.org/document/6465188,

https://dblp.uni-trier.de/db/conf/wsc/wsc2012.html#BartaRSG12,

http://repository.supsi.ch/3940,

https://www.informs-sim.org/wsc12papers/includes/files/inv111.pdf,

https://dl.acm.org/citation.cfm?id=2430145,

https://doi.org/10.1109/WSC.2012.6465188,

https://academic.microsoft.com/#/detail/2170359740