Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Train Dispatching
Optrail, ITA.
Universitetet i Oslo, NOR.
Universita degli Studi Roma Tre, ITA.
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
2018 (English)In: Handbook of Optimization in the Railway Industry / [ed] Borndörfer, R. (et al.), Springer New York LLC , 2018, 268, p. 265-283Chapter in book (Refereed)
Abstract [en]

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 and constraints to consider. This chapter defines the problem and summarizes the variety of model types and solution approaches developed over the years, in order to address and solve the train dispatching problem from the infrastructure manager perspective. Despite all the research efforts, it is, however, only very recently that the railway industry has made significant attempts to explore the large potential in using optimization-based decision-support to facilitate railway traffic disturbance management. This chapter reviews state-of-practice and provides a discussion about the observed slow progress in the application of optimization-based methods in practice. A few successful implementations have been identified, but their performance as well as the lessons learned from the development and implementation of those system are unfortunately only partly available to the research community, or potential industry users. © 2018, Springer International Publishing AG.

Place, publisher, year, edition, pages
Springer New York LLC , 2018, 268. p. 265-283
Series
International Series in Operations Research and Management Science, ISSN 0884-8289 ; 268
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:bth-16026DOI: 10.1007/978-3-319-72153-8_12Scopus ID: 2-s2.0-85043258670ISBN: 978-3-319-72153-8 (print)OAI: oai:DiVA.org:bth-16026DiVA, id: diva2:1193026
Available from: 2018-03-26 Created: 2018-03-26 Last updated: 2018-03-26Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records BETA

Törnquist Krasemann, Johanna

Search in DiVA

By author/editor
Törnquist Krasemann, Johanna
By organisation
Department of Computer Science and Engineering
Computer Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 29 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf