Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • 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
Simulation of planning strategies for track allocation at marshalling yards
RISE - Research Institutes of Sweden (2017-2019), ICT, SICS.ORCID iD: 0000-0003-1597-6738
RISE, Swedish ICT, SICS.ORCID iD: 0000-0003-4456-9453
KTH Royal Institute of Technology, Sweden.
2013 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Planning the operational procedures in a railway marshalling yard is a complex problem. When a train arrives at a marshalling yard, it is uncoupled at an arrival yard and then its cars are rolled to a classification yard. All cars should eventually be rolled to the classification track that has been assigned to the train they're supposed to depart with. However, there is normally not enough capacity to compound all trains at once. In Sweden, cars arriving before a track has been assigned to their train can be stored on separate tracks called mixing tracks. All cars on mixing tracks will be pulled back to the arrival yard, and then rolled to the classification yard again to allow for reclassification. Today all procedures are planned by experienced dispatchers, but there are no documented strategies or guidelines for efficient manual planning. The aim of this paper is to examine operational planning strategies that could help dispatchers find a feasible marshalling schedule that minimizes unnecessary mixing. In order to achieve this goal, two different online planning strategies have been tested using deterministic and stochastic simulation. The Hallsberg marshalling yard was used as a case study, and was simulated for the time period between December 2010 and May 2011. The first tested strategy simply assigns tracks to trains on a first come-first served basis, while the second strategy uses time limits to determine when tracks should be assigned to departing trains. The online planning algorithms have been compared with an offline optimized track allocation. The results from both the deterministic and the stochastic simulation show that the optimized allocation is better than all online strategies and that the second strategy with a time limit of 32 hours is the best online method.

Place, publisher, year, edition, pages
2013, 11. Vol. 55, p. 465-475
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:ri:diva-24076DOI: 10.2495/CMEM130381Scopus ID: 2-s2.0-84887595424OAI: oai:DiVA.org:ri-24076DiVA, id: diva2:1043155
Conference
13th International Conference on Design and Operation in Railway Engineering
Projects
RANPLANAvailable from: 2016-10-31 Created: 2016-10-31 Last updated: 2023-06-07Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Bohlin, MarkusGestrelius, Sara

Search in DiVA

By author/editor
Bohlin, MarkusGestrelius, Sara
By organisation
SICSSICS
Computer and Information Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 258 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • 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