Online railway delay management: Hardness, simulation and computation

dc.contributor.authorBerger, André
dc.contributor.authorHoffmann, Ralf
dc.contributor.authorLorenz, Ulf
dc.contributor.authorStiller, Sebastian
dc.date.accessioned2019-01-08T17:30:59Z
dc.date.available2019-01-08T17:30:59Z
dc.date.issued2011
dc.descriptionDieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.de
dc.descriptionThis publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.en
dc.description.abstractDelays in a railway network are a common problem that railway companies face in their daily operations. When a train is delayed, it may either be beneficial to let a connecting train wait so that passengers in the delayed train do not miss their connection, or it may be beneficial to let the connecting train depart on time to avoid further delays. These decisions naturally depend on the global structure of the network, on the schedule, on the passenger routes and on the imposed delays. The railway delay management (RDM) problem (in a broad sense) is to decide which trains have to wait for connecting trains and which trains have to depart on time. The offline version (i.e. when all delays are known in advance) is already NP-hard for very special networks. In this paper we show that the online railway delay management (ORDM) problem is PSPACE-hard. This result justifies the need for a simulation approach to evaluate wait policies for ORDM. For this purpose we present TOPSU—RDM, a simulation platform for evaluating and comparing different heuristics for the ORDM problem with stochastic delays. Our novel approach is to separate the actual simulation and the program that implements the decision-making policy, thus enabling implementations of different heuristics to ‘‘compete’’ on the same instances and delay distributions. We also report on computational results indicating the worthiness of developing intelligent wait policies. For RDM and other logistic planning processes, it is our goal to bridge the gap between theoretical models, which are accessible to theoretical analysis, but are often too far away from practice, and the methods which are used in practice today, whose performance is almost impossible to measure.en
dc.description.sponsorshipEU/FP6/021235-2/EU/Algorithms for Robust and on-line Railway optimisation: Improving the validity and reliability of large-scale systems/ARRIVALen
dc.identifier.eissn1741-3133
dc.identifier.issn0037-5497
dc.identifier.urihttps://depositonce.tu-berlin.de/handle/11303/8830
dc.identifier.urihttp://dx.doi.org/10.14279/depositonce-7959
dc.language.isoen
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subject.ddc004 Datenverarbeitung; Informatikde
dc.subject.otheronline railway delay managementen
dc.subject.otherweb-based simulationen
dc.subject.otherdiscrete event simulationen
dc.subject.otherPSPACEen
dc.titleOnline railway delay management: Hardness, simulation and computationen
dc.typeArticleen
dc.type.versionpublishedVersionen
dcterms.bibliographicCitation.doi10.1177/0037549710373571
dcterms.bibliographicCitation.issue7
dcterms.bibliographicCitation.journaltitleSimulation : transactions of The Society for Modeling and Simulation Internationalen
dcterms.bibliographicCitation.originalpublishernameSAGE Publicationsen
dcterms.bibliographicCitation.originalpublisherplaceWashington, DCen
dcterms.bibliographicCitation.pageend629
dcterms.bibliographicCitation.pagestart616
dcterms.bibliographicCitation.volume87
tub.accessrights.dnbdomain
tub.affiliationFak. 2 Mathematik und Naturwissenschaften::Inst. Mathematikde
tub.affiliation.facultyFak. 2 Mathematik und Naturwissenschaftende
tub.affiliation.instituteInst. Mathematikde
tub.publisher.universityorinstitutionTechnische Universität Berlinde

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