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  • 1.
    Bohlin, Markus
    et al.
    Swedish Institute of Computer Science, Sweden.
    Dahms, FlorianRWTH Aachen, Chair of Operations Research, Germany.Flier, HolgerETH Zürich, Institute of Theoretical Computer Science, Switzerland.Sara, GestreliusSwedish Institute of Computer Science, Sweden.
    Optimal Freight Train Classification using Column Generation2012Collection (editor) (Refereed)
  • 2.
    Bohlin, Markus
    et al.
    SICS Swedish ICT AB, Sweden.
    Gestrelius, Sara
    SICS Swedish ICT AB, Sweden.
    Dahms, Florian
    RWTH Aachen University, Germany.
    Mihalák, Matúš
    ETH Zürich, Switzerland.
    Flier, Holger
    ETH Zürich, Switzerland.
    Optimization Methods for Multistage Freight Train Formation2015In: Transportation Science, ISSN 0041-1655, E-ISSN 1526-5447, Vol. 50, no 3, p. 823-840Article in journal (Refereed)
  • 3.
    Bohlin, Markus
    et al.
    SICS Swedish ICT, Kista, Sweden.
    Gestrelius, Sara
    SICS Swedish ICT, Kista, Sweden.
    Fahimeh, Khoshniyat
    SICS Swedish ICT, Kista, Sweden.
    Simulation of planning strategies for track allocation at marshalling yards2013In: WIT Transactions on Modelling and Simulation, Volume 55, 2013, Ashurst, Southampton: WIT Press, 2013, Vol. 55, p. 465-475Conference 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.

  • 4.
    Gestrelius, Sara
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Mathematical models for optimising decision support systems in the railway industry2015Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    After the deregulation of the Swedish railway industry, train operating companies compete for and on the same infrastructure. This makes the allocation of rail capacity a most delicate problem, and for a well-functioning railway system the allocation must be fair, efficient and functional. The capacity allocation tasks include e.g. constructing the yearly timetable and making track allocation plans for rail yards. The state of practice is that experienced planners construct the schedules manually with little or no decision support. However, as the planners are often faced with large combinatorial problems that are notoriously hard to solve there is a great potential in implementing optimising decision support systems. The research presented in this licentiate thesis aims at developing and examining mathematical models and methods that could be part of such support systems. The thesis focuses on two planning problems in particular, and the presented methods have been developed especially for the Swedish railway system. First of all, a model for optimising a train timetable with respect to robustness is presented. The model tries to increase the number of alternative meeting locations that can be used in a disturbed traffic situation and has an execution time of less than 5 minutes when solving the problem for the track section between Boden and Vännäs.                                                                                                                Secondly, the problem of generating efficient classification bowl schedules for shunting yards is examined. The aim is to find the track allocation that minimises the number of required shunting movements while still respecting all operational, physical and time constraints imposed by the yard.  Three optimisation models are presented, and simple planning rules are also investigated. The methods are tested on historic data from Hallsberg, the largest shunting yard in Sweden, and the results show that while the simple planning rules are not adequate for planning the classification bowl, two of the optimisation models consistently return an optimal solution within an acceptable execution time.

  • 5.
    Gestrelius, Sara
    et al.
    SICS Swedish ICT AB, Sweden.
    Dahms, Florian
    RWTH Aachen, Germany.
    Bohlin, Markus
    SICS Swedish ICT AB, Sweden.
    Optimisation of simultaneous train formation and car sorting ar marshalling yards2013In: Proceedings of the 5th International Seminar on Railway Operations modelling and Analysis (RailCopenhagen), Monday 13 May 2013 - Wednesday 15 May 2013 Technical University of Denmark, 2013Conference paper (Refereed)
  • 6.
    Gestrelius, Sara
    et al.
    SICS Swedish ICT AB, Sweden.
    Dahms, Florian
    RWTH Aachen, Germany.
    Bohlin, Markus
    SICS Swedish ICT AB, Sweden.
    Optimisation of simultaneous train formation and car sorting at marshalling yards2013In: Proceedings of the 5th International Conference on Railway Operations Modelling and Analysis IAROR13, 2013Conference paper (Refereed)
    Abstract [en]

    Efficient and correct freight train marshalling is vital for high quality carload freight transportations. During marshalling, it is desirable that cars are sorted according to their individual drop-off locations in the outbound freight trains. Furthermore, practical limitations such as non-uniform and limited track lengths and the arrival and departure times of trains need to be considered. This paper presents a novel optimisation method for freight marshalling scheduling under these circumstances. The method is based on an integer programming formulation that is solved using column generation and branch and price. The approach minimises the number of extra shunting operations that have to be performed, and is evaluated on real-world data from the Hallsberg marshalling yard in Sweden.

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