Please use this identifier to cite or link to this item: http://hdl.handle.net/11718/23950
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dc.contributor.authorNarayanaswami, Sundaravalli-
dc.date.accessioned2021-05-29T09:35:25Z-
dc.date.available2021-05-29T09:35:25Z-
dc.date.issued2019-
dc.identifier.citationNarayanaswami, S. (2019). Optimal allocation of rolling stock in scheduled transportation services. International Journal of Logistics Systems and Management, 34(3). doi:https://doi.org/10.1504/IJLSM.2019.103087en_US
dc.identifier.issn17427967 (Print)-
dc.identifier.issn17427975 (Online)-
dc.identifier.urihttp://hdl.handle.net/11718/23950-
dc.description.abstractPassenger railway transportation services are operated in cyclic periodicities for urban and long distance traffic. Cabins and locomotives (rakes) are assigned to each service for specified time duration to operationalise timetables. Such resource allocations are generally constrained and incur cost, each in travel time, empty cabin runs and rake compositions. Some constraints are safety related and others are desirable for performance improvement. Resource utilisation is effective, if demands are met; efficient, if utilisation cost is minimum. A multi-commodity network flow model is presented to optimally allocate rolling stock, to fulfil demands at minimum operational cost. However, the model is computationally expensive and a relaxed model using simulation based heuristic is presented. Real data from Indian railways is used for testing. The problem context, model, heuristic approach and solutions are reported. Managerial insights that emerged from this empirical study are interesting; we present them along with limitations and possible extensions.en_US
dc.language.isoenen_US
dc.publisherInternational Journal of Logistics Systems and Managementen_US
dc.subjectOR in service industriesen_US
dc.subjectRolling stocken_US
dc.subjectOptimal allocationen_US
dc.subjectNetwork flow modelen_US
dc.subjectSimulation-based heuristicen_US
dc.titleOptimal allocation of rolling stock in scheduled transportation servicesen_US
dc.typeArticleen_US
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