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http://hdl.handle.net/11718/23599
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DC Field | Value | Language |
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dc.contributor.author | Roy, Debjit | - |
dc.contributor.author | Koster, Rene De | - |
dc.date.accessioned | 2021-02-16T05:14:01Z | - |
dc.date.available | 2021-02-16T05:14:01Z | - |
dc.date.issued | 2015-04 | - |
dc.identifier.citation | Roy, Debjit. & Koster, Rene De. (2015). Stochastic modelling of unloading and loading operations at a container terminal using automated lifting vehicles. SSRN. | en_US |
dc.identifier.uri | http://hdl.handle.net/11718/23599 | - |
dc.description.abstract | With growing worldwide trade, container terminals have grown in number and size. Many new terminals are now automated to increase operational efficiency. The key focus is on improving seaside processes, where a distinction can be made between single quay crane operations (all quay cranes are either loading or unloading containers) and overlapping quay crane operations (some quay cranes are loading while others are unloading containers). From existing studies, it is not clear if the design insights obtained from analyzing single operations, such as optimal stack layout, are consistent with the insights obtained from analyzing overlapping operations. In this paper, we develop new integrated stochastic models for analyzing the performance of overlapping loading and unloading operations that capture the complex stochastic interactions among quayside, vehicle, and stackside processes. Using these integrated models, we are able to show that that there are stack layout configurations that are robust for both single (either loading or unloading) and for overlapping (both loading and unloading) operations. | en_US |
dc.language.iso | en | en_US |
dc.publisher | SSRN | en_US |
dc.subject | logistics | en_US |
dc.subject | queuing | en_US |
dc.subject | transportation | en_US |
dc.subject | uncertainty modelling | en_US |
dc.title | Stochastic modelling of unloading and loading operations at a container terminal using automated lifting vehicles | en_US |
dc.type | Working Paper | en_US |
Appears in Collections: | Working Papers |
Files in This Item:
File | Description | Size | Format | |
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SSRN-id2599593.pdf | SSRN-id2599593 | 1.63 MB | Adobe PDF | View/Open |
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