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dc.contributor.advisorStephen Graves and Chris Caplice.en_US
dc.contributor.authorBall, Braden (Braden R.)en_US
dc.contributor.otherLeaders for Global Operations Program.en_US
dc.date.accessioned2012-09-27T15:27:04Z
dc.date.available2012-09-27T15:27:04Z
dc.date.copyright2012en_US
dc.date.issued2012en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/73378
dc.descriptionThesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division; in conjunction with the Leaders for Global Operations Program at MIT, 2012.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (p. 54-55).en_US
dc.description.abstractCompanies that utilize multiple facilities to satisfy customer demand are faced with the same basic question - where should inventory be held? This thesis presents a method for answering this question, specifically for a company that allocates multiple units across multiple facilities, where any facility can fulfill an order to any customer, though with differing shipping costs. The model presented is a simulation of the shipping costs of various allocation strategies across a range of allocated inventory quantities, where the strategies simulated include consolidating all inventory in a central facility, constraining inventory to regional hubs, and spreading inventory throughout the network. The simulated results are then compared to find the low cost allocation strategy at a given level of allocated inventory. With this comparison, product groupings with the same low cost allocation strategy are identified, and are defined as "Slow", "Medium-A", "Medium-B", and "Fast" products. These groups can then be used to manage the allocation process, where "Slow" inventory is held centrally, "Medium-A" inventory held regionally, and "Fast" inventory spread throughout the network. "Medium-B" items serve as a costmitigating flexible option, where they are spread throughout the network when possible but consolidated when necessary to avoid changing the allocation for "Fast" items. At a broad level, the model presented is applicable to any company that can fulfill demand to a single customer from multiple facilities.en_US
dc.description.statementofresponsibilityby Braden Ball.en_US
dc.format.extent55 p.en_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectSloan School of Management.en_US
dc.subjectEngineering Systems Division.en_US
dc.subjectLeaders for Global Operations Program.en_US
dc.titleSimulation as a Method for Determining Inventory Classifications for allocationen_US
dc.typeThesisen_US
dc.description.degreeS.M.en_US
dc.description.degreeM.B.A.en_US
dc.contributor.departmentLeaders for Global Operations Program at MITen_US
dc.contributor.departmentMassachusetts Institute of Technology. Engineering Systems Division
dc.contributor.departmentSloan School of Management
dc.identifier.oclc809793923en_US


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