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Evaluation of planning policies for marshalling track allocation using simulation
RISE - Research Institutes of Sweden (2017-2019), SICS, Sweden.ORCID iD: 0000-0003-1597-6738
RISE., SICS.ORCID iD: 0000-0003-4456-9453
2012 (English)Report (Other academic)
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 on 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
Kista, Sweden: Swedish Institute of Computer Science , 2012, 10.
Keywords [en]
Railways, Marshalling, Marshalling yards, Simulation
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:mdh:diva-61243OAI: oai:DiVA.org:mdh-61243DiVA, id: diva2:1719229
Projects
RanPlan
Note

This work has been done at SICS and it is also a part of the dissertation submitted to KTH, Royal Institute of Technology division of traffic and logistics, railway group, to be granted a master of science degree in "Transport Systems.

Available from: 2022-12-14 Created: 2022-12-14 Last updated: 2022-12-14Bibliographically approved

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Bohlin, MarkusGestrelius, Sara

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CiteExportLink to record
Permanent link

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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