2026-09-19T06:51:54Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/733782022-01-27T21:17:31Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Stephen Graves and Chris Caplice.
Ball, Braden (Braden R.)
Leaders for Global Operations Program.
Leaders for Global Operations Program at MIT
Massachusetts Institute of Technology. Engineering Systems Division
Sloan School of Management
2012-09-27T15:27:04Z
2012-09-27T15:27:04Z
2012
2012
http://hdl.handle.net/1721.1/73378
809793923
Thesis (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.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 54-55).
Companies 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.
by Braden Ball.
S.M.
M.B.A.
55 p.
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by
copyright. They may be viewed from this source for any purpose, but
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http://dspace.mit.edu/handle/1721.1/7582
Sloan School of Management.
Engineering Systems Division.
Leaders for Global Operations Program.
Simulation as a Method for Determining Inventory Classifications for allocation
Thesis
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Publication
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<Abstract>Companies 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.</Abstract>
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