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dc.contributor.authorEaton, Jayneen
dc.contributor.authorYang, Shengxiangen
dc.contributor.authorMavrovouniotis, Michalisen
dc.date.accessioned2016-04-13T14:59:09Z
dc.date.available2016-04-13T14:59:09Z
dc.date.issued2015-11
dc.identifier.citationEaton, J., Yang,S. and Mavrovouniotis, M. (2015) Ant colony optimization with immigrants schemes for the dynamic railway junction rescheduling problem with multiple delays. Soft Computing, 20 (8), pp. 2951-2966en
dc.identifier.urihttp://hdl.handle.net/2086/11883
dc.description.abstractTrain rescheduling after a perturbation is a challenging task and is an important concern of the railway industry as delayed trains can lead to large fines, disgruntled customers and loss of revenue. Sometimes not just one delay but several unrelated delays can occur in a short space of time which makes the problem even more challenging. In addition, the problem is a dynamic one that changes over time for, as trains are waiting to be rescheduled at the junction, more timetabled trains will be arriving, which will change the nature of the problem. The aim of this research is to investigate the application of several different ant colony optimization (ACO) algorithms to the problem of a dynamic train delay scenario with multiple delays. The algorithms not only resequence the trains at the junction but also resequence the trains at the stations, which is considered to be a first step towards expanding the problem to consider a larger area of the railway network. The results show that, in this dynamic rescheduling problem, ACO algorithms with a memory cope with dynamic changes better than an ACO algorithm that uses only pheromone evaporation to remove redundant pheromone trails. In addition, it has been shown that if the ant solutions in memory become irreparably infeasible it is possible to replace them with elite immigrants, based on the best-so-far ant, and still obtain a good performance.en
dc.language.isoen_USen
dc.publisherSpringeren
dc.subjectDynamic railway junction reschedulingen
dc.subjectAnt colony optimizationen
dc.subjectUK railway networken
dc.subjectRail transportationen
dc.subjectDynamic optimization problemen
dc.titleAnt colony optimization with immigrants schemes for the dynamic railway junction rescheduling problem with multiple delaysen
dc.typeArticleen
dc.identifier.doihttp://dx.doi.org/10.1007/s00500-015-1924-x
dc.researchgroupCentre for Computational Intelligenceen
dc.peerreviewedYesen
dc.explorer.multimediaNoen
dc.funderEPSRC (Engineering and Physical Sciences Research Council)en
dc.projectidEP/K001310/1en
dc.cclicenceCC-BY-NC-NDen
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en


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