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dc.contributor.authorFang, W.en
dc.contributor.authorYang, Shengxiangen
dc.contributor.authorYao, Xinen
dc.date.accessioned2016-01-14T10:24:25Z
dc.date.available2016-01-14T10:24:25Z
dc.date.issued2015-12-01
dc.identifier.citationFang, W., Yang, S. and Yao, X. (2015) A survey on problem models and solution approaches to rescheduling in railway networks. IEEE Transactions on Intelligent Transportation Systems, 16 (6), pp. 2997-3016en
dc.identifier.issn1524-9050
dc.identifier.urihttp://hdl.handle.net/2086/11471
dc.description.abstractRescheduling in railway networks is a challenging problem in both practice and theory. It requires good quality solutions in reasonable computation time to resolve unexpected situations, involving different problem scales, railway network infrastructures, objectives, and constraints. This paper presents a comprehensive survey on different problem models for rescheduling in railway networks by a clear classification. Some frequently used models are described in detail through reviewing their variables and constraints. This paper also focuses on the solution approaches proposed in the literature. The main ideas of the solution approaches with the objectives are described. Based on our review results, the analysis of the problem models used in various problem types and the solution approaches used in different problem models are presented. Conclusion and suggestions for further research to rescheduling in railway networks are drawn toward the end of the paper.en
dc.language.isoen_USen
dc.publisherIEEE Pressen
dc.subjectReschedulingen
dc.subjectalternative graphsen
dc.subjectheuristicsen
dc.subjectmeta-heuristicsen
dc.subjectmixed-integer programmingen
dc.subjectrailway networksen
dc.titleA survey on problem models and solution approaches to rescheduling in railway networksen
dc.typeArticleen
dc.identifier.doihttp://dx.doi.org/10.1109/TITS.2015.2446985
dc.researchgroupCentre for Computational Intelligenceen
dc.peerreviewedYesen
dc.funderEPSRC (Engineering and Physical Sciences Research Council)en
dc.projectidEP/K001310/1en
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en


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