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http://hdl.handle.net/11375/20483
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DC Field | Value | Language |
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dc.contributor.advisor | Huang, Kai | - |
dc.contributor.author | E, Fan | - |
dc.date.accessioned | 2016-09-23T19:40:36Z | - |
dc.date.available | 2016-09-23T19:40:36Z | - |
dc.date.issued | 2016 | - |
dc.identifier.uri | http://hdl.handle.net/11375/20483 | - |
dc.description.abstract | In this paper, a two-stage stochastic facility location problem integrated with inven- tory and recourse decisions is studied and solved. This problem is inspired by an industrial supply chain design problem of a large retail chain with slow-moving prod- ucts. Uncertainty is expressed by a discrete and finite set of scenarios. Recourse actions can be taken after the realization of random demands. Location, inventory, transportation, and recourse decisions are integrated into a mixed-integer program with an objective minimizing the expected total cost. A dual heuristic procedure is studied and embedded into the sample average approximation (SAA) method. The computation experiments demonstrate that our combined SAA with dual heuristic algorithm has a similar performance on solution quality and a much shorter compu- tational time. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | stochastic facility location problem; | en_US |
dc.subject | sample average approximation | en_US |
dc.subject | dual heuristic | en_US |
dc.subject | location-inventory problem | en_US |
dc.title | A Location-Inventory Problem for Customers with Time Constraints | en_US |
dc.type | Article | en_US |
dc.contributor.department | Computational Engineering and Science | en_US |
dc.description.degreetype | Thesis | en_US |
dc.description.degree | Master of Applied Science (MASc) | en_US |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Description | Size | Format | |
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E_Fan_201608_Master's.pdf | 364.77 kB | Adobe PDF | View/Open |
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