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Mathematical models for optimising decision support systems in the railway industry
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
2015 (English)Licentiate 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.

Place, publisher, year, edition, pages
Västerås: Mälardalen University , 2015.
Series
Mälardalen University Press Licentiate Theses, ISSN 1651-9256 ; 196
National Category
Other Computer and Information Science
Identifiers
URN: urn:nbn:se:mdh:diva-27758ISBN: 978-91-7485-196-0 (print)OAI: oai:DiVA.org:mdh-27758DiVA: diva2:798558
Presentation
2015-04-28, Mälardalens högskola, Västerås, 13:30
Opponent
Available from: 2015-03-27 Created: 2015-03-27 Last updated: 2015-04-23Bibliographically approved
List of papers
1. On the delivery robustness of train timetables with respect to production replanning possibilities
Open this publication in new window or tab >>On the delivery robustness of train timetables with respect to production replanning possibilities
2012 (English)In: Proceedings of the 2nd International Conference on Road and Rail Infrastructure (CETRA), Dubrovnik, Croatia, 2012, 823-830 p.Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
Dubrovnik, Croatia: , 2012
National Category
Other Computer and Information Science
Identifiers
urn:nbn:se:mdh:diva-27753 (URN)978-953-6272-50-1 (ISBN)
Conference
CETRA 2012, 2nd International Conference on Road and Rail Infrastructure, 7–9 May 2012, Dubrovnik, Croatia
Available from: 2015-03-27 Created: 2015-03-27 Last updated: 2015-03-27Bibliographically approved
2. Optimal Freight Train Classification using Column Generation
Open this publication in new window or tab >>Optimal Freight Train Classification using Column Generation
2012 (English)Collection (editor) (Refereed)
Place, publisher, year, edition, pages
Dagsthul, Germany: Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, 2012
Series
OASICS, ISSN 2190-6807
National Category
Other Computer and Information Science
Identifiers
urn:nbn:se:mdh:diva-27754 (URN)
Available from: 2015-03-27 Created: 2015-03-27 Last updated: 2015-03-27Bibliographically approved
3. Simulation of planning strategies for track allocation at marshalling yards
Open this publication in new window or tab >>Simulation of planning strategies for track allocation at marshalling yards
2013 (English)In: WIT Transactions on Modelling and Simulation, Volume 55, 2013, Ashurst, Southampton: WIT Press, 2013, Vol. 55, 465-475 p.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
Ashurst, Southampton: WIT Press, 2013
National Category
Other Computer and Information Science
Identifiers
urn:nbn:se:mdh:diva-27755 (URN)10.2495/CMEM130381 (DOI)2-s2.0-84887595424 (Scopus ID)978-184564732-2 (ISBN)
Conference
16th International Conference on Computational Methods and Experimental Measurements, CMEM 2013; A Coruna; Spain; 2 July 2013 through 4 July 2013;
Available from: 2015-03-27 Created: 2015-03-27 Last updated: 2015-04-15Bibliographically approved
4. Optimisation of simultaneous train formation and car sorting ar marshalling yards
Open this publication in new window or tab >>Optimisation of simultaneous train formation and car sorting ar marshalling yards
2013 (English)In: 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, Published paper (Refereed)
National Category
Other Computer and Information Science
Identifiers
urn:nbn:se:mdh:diva-27756 (URN)
Conference
5th International Seminar on Railway Operations modelling and Analysis (RailCopenhagen)
Available from: 2015-03-27 Created: 2015-03-27 Last updated: 2015-03-27Bibliographically approved
5. Optimization Methods for Multistage Freight Train Formation
Open this publication in new window or tab >>Optimization Methods for Multistage Freight Train Formation
Show others...
2015 (English)In: Transportation Science, ISSN 0041-1655, E-ISSN 1526-5447, Vol. 50, no 3, 823-840 p.Article in journal (Refereed) Published
National Category
Other Computer and Information Science
Identifiers
urn:nbn:se:mdh:diva-27757 (URN)10.1287/trsc.2014.0580 (DOI)2-s2.0-84984866208 (Scopus ID)
Available from: 2015-03-27 Created: 2015-03-27 Last updated: 2016-09-20Bibliographically approved

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