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dc.contributor.authorEaton, Jayneen
dc.contributor.authorYang, Shengxiangen
dc.date.accessioned2016-11-04T11:31:30Z
dc.date.available2016-11-04T11:31:30Z
dc.date.issued2016-12
dc.identifier.citationEaton, J. and Yang, S. (2016) Railway platform reallocation after dynamic perturbations using ant colony optimisation. Proceedings of the 2016 IEEE Symposium Series on Computational Intelligence, 2016en
dc.identifier.urihttp://hdl.handle.net/2086/12781
dc.descriptionThe file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.en
dc.description.abstractTrain delays at stations are a common occurrence in complex, busy railway networks. A delayed train will miss its scheduled time slot on the platform and may have to be reallocated to a new platform to allow it to continue its journey. The problem is a dynamic one because while reallocating a delayed train further unanticipated train delays may occur, changing the nature of the problem over time. Our aim in this study is to apply ant colony optimisation (ACO) to a dynamic platform reallocation problem (DPRP) using a model created from real-world train schedule data. To ensure that trains are not unnecessarily reallocated to new platforms we introduce a novel best-ant-replacement scheme that takes into account not only the objective value but also the physical distance between the original and the new platforms. Results showed that the ACO algorithm outperformed a heuristic that places the delayed train in the first available time-slot and that this improvement was more apparent with high-frequency dynamic changes.en
dc.language.isoen_USen
dc.publisherIEEEen
dc.titleRailway platform reallocation after dynamic perturbations using ant colony optimisationen
dc.typeConferenceen
dc.identifier.doihttps://doi.org/10.1109/ssci.2016.7849965
dc.researchgroupCentre for Computational Intelligenceen
dc.peerreviewedYesen
dc.funderEngineering and Physical Sciences Research Council (EPSRC)en
dc.projectidEP/K001310/1en
dc.cclicenceCC-BY-NCen
dc.date.acceptance2016-09-27en
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en


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