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dc.contributor.authorRoy, Debjit
dc.contributor.authorParhi, Sampanna
dc.contributor.authorGupta, Akash
dc.contributor.authorParhi, Sampanna
dc.date.accessioned2017-06-23T09:34:11Z
dc.date.available2017-06-23T09:34:11Z
dc.date.issued2017
dc.identifier.citationGupta A., Roy D., de Koster R., Parhi S. (2017). Optimal stack layout in a sea container terminal with automated lifting vehicles. International Journal of Production Research, 55(13), 3747-3765.en_US
dc.identifier.urihttp://hdl.handle.net/11718/19622
dc.description.abstractContainer terminal performance is largely determined by its design decisions, which include the number and type of quay cranes, stack cranes, transport vehicles, vehicle travel path and stack layout. We investigate the orientation of the stack layout (parallel or perpendicular to the quayside) on the throughput time performance of the terminals. Previous studies in this area typically use deterministic optimisation, and a few studies use probabilistic travel times and simulation to analyse the effect of stack layout on terminal throughput times. In this research, we capture the stochasticity with an integrated queuing network modelling approach to analyse the performance of container terminals with parallel stack layout using automated lifting vehicles. Using this analytical model, we investigate 1008 parallel stack layout configurations on throughput times and determine the optimal stack layout configuration. We find that, assuming an identical width of the internal transport area, container terminals with parallel stack layout perform better (from 4–12% in terms of container throughput times) than terminals with a perpendicular stack layout.en_US
dc.language.isoen_USen_US
dc.publisherTaylor and Francis Ltd.en_US
dc.subjectContainer terminalen_US
dc.subjectFacility layouten_US
dc.subjectParallel vs. perpendicular stack layouten_US
dc.subjectQueuing modelsen_US
dc.subjectSimulationen_US
dc.titleOptimal stack layout in a sea container terminal with automated lifting vehiclesen_US
dc.typeArticleen_US


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