Barons, Martine J. (2021) Strategies for the use of data and algorithm approaches in railway traffic management. Working Paper. Cambridge Open Engage. Mathematics In Industry Reports .

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Abstract

Resonate are interested in looking at different strategies / models / techniques for dealing with the problem of rescheduling a railway timetable when it's unexpectedly disrupted, the likely strengths and risks of these, and how they might be adapted to improve existing solutions. Nine different approaches (drawn from machine learning, network models and stochastic models) to defining the efficiency of a station in dissipating delays were considered. They fell broadly into two groups: those that sought to understand the propagation of delays and those that sought to offer strategies for minimising delays.

Item Type:	Working or Discussion Paper (Working Paper)
Subjects:	H Social Sciences > HE Transportation and Communications Q Science > Q Science (General) Q Science > QA Mathematics T Technology > T Technology (General) T Technology > TF Railroad engineering and operation
Divisions:	Faculty of Science > Statistics
Library of Congress Subject Headings (LCSH):	Railroads -- Traffic -- Mathematical models , Railroads -- Management -- Mathematical models , Machine learning, Bayesian statistical decision theory , Integer programming
Series Name:	Mathematics In Industry Reports
Publisher:	Cambridge Open Engage
Official Date:	28 June 2021
Dates:	Date Event 28 June 2021 Published September 2017 Accepted
Number of Pages:	69
Institution:	University of Warwick
Status:	Not Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Open Access
Open Access Version:	Publisher

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