Determining operations affected by delay in predictive train timetables

Burdett, Robert L. & Kozan, Erhan (2014) Determining operations affected by delay in predictive train timetables. Computers and Operations Research, 41, pp. 150-166.

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Constructing train schedules is vital in railways. This complex and time consuming task is however made more difficult by additional requirements to make train schedules robust to delays and other disruptions. For a timetable to be regarded as robust, it should be insensitive to delays of a specified level and its performance with respect to a given metric, should be within given tolerances. In other words the effect of delays should be identifiable and should be shown to be minimal. To this end, a sensitivity analysis is proposed that identifies affected operations. More specifically a sensitivity analysis for determining what operation delays cause each operation to be affected is proposed. The information provided by this analysis gives another measure of timetable robustness and also provides control information that can be used when delays occur in practice. Several algorithms are proposed to identify this information and they utilise a disjunctive graph model of train operations. Upon completion the sets of affected operations can also be used to define the impact of all delays without further disjunctive graph evaluations.

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4 citations in Web of Science®

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ID Code: 61861
Item Type: Journal Article
Refereed: Yes
DOI: 10.1016/j.cor.2013.08.011
ISSN: 1873-765X
Subjects: Australian and New Zealand Standard Research Classification > MATHEMATICAL SCIENCES (010000) > OTHER MATHEMATICAL SCIENCES (019900)
Australian and New Zealand Standard Research Classification > MATHEMATICAL SCIENCES (010000) > OTHER MATHEMATICAL SCIENCES (019900) > Mathematical Sciences not elsewhere classified (019999)
Divisions: Current > Schools > School of Mathematical Sciences
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2013 Elsevier Ltd.
Copyright Statement: This is the author’s version of a work that was accepted for publication in Computers and Operations Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computers and Operations Research, [Volume 41, (January 2014)] DOI: 10.1016/j.cor.2013.08.011
Deposited On: 18 Aug 2013 21:38
Last Modified: 31 Jul 2015 19:13

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