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dc.contributor.advisorHermano Igo Krebs and Jónas Oddur.en_US
dc.contributor.authorHe, Denton(Denton Xiang)en_US
dc.contributor.otherSloan School of Management.en_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Mechanical Engineering.en_US
dc.contributor.otherLeaders for Global Operations Program.en_US
dc.date.accessioned2020-09-03T15:51:43Z
dc.date.available2020-09-03T15:51:43Z
dc.date.copyright2020en_US
dc.date.issued2020en_US
dc.identifier.urihttps://hdl.handle.net/1721.1/126902
dc.descriptionThesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, in conjunction with the Leaders for Global Operations Program at MIT, May, 2020en_US
dc.descriptionThesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, in conjunction with the Leaders for Global Operations Program at MIT, May, 2020en_US
dc.descriptionCataloged from the official PDF of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 72-73).en_US
dc.description.abstractAs companies expand and innovate, it is sometimes prudent to be conservative when incorporating new products and technologies. Instead of constructing buildings to store new products, firms may look to optimize re-allocation of space within existing facilities to fit more products and save on one-time capital outlay. In this research, the Distribution Center (which also picks and packs products according to incoming orders) is looking to optimize utilization of offsite storage (and transportation) costs in the face of growing product demand. The DC is situated in a region of High Real Estate cost, and there is potential to increase utilization of offsite leased storage at Low Real Estate cost areas. To investigate potential changes, research will be divided into two parts: Part One looks to optimize product storage within the current Distribution Center and Offsite Warehouse network, by developing a model that incorporates product demand, product sizes and replenishment frequency. Part Two utilizes the built model to investigate alternative offsite solutions, taking into consideration Real Estate costs, transportation frequency and other factors. Previous research papers have looked at the two parts separately, whilst this research aims to link the two parts together. Finally, a simple and easy to use decision-support tool was developed that allows users to periodically review and adjust product allocation based on product information, demand and Real Estate costs.en_US
dc.description.statementofresponsibilityby Denton He.en_US
dc.format.extent77 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectSloan School of Management.en_US
dc.subjectMechanical Engineering.en_US
dc.subjectLeaders for Global Operations Program.en_US
dc.titleDistribution and replenishment optimization between locations of high and low real estate costen_US
dc.typeThesisen_US
dc.description.degreeM.B.A.en_US
dc.description.degreeS.M.en_US
dc.contributor.departmentSloan School of Managementen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineeringen_US
dc.contributor.departmentLeaders for Global Operations Programen_US
dc.identifier.oclc1191623451en_US
dc.description.collectionM.B.A. Massachusetts Institute of Technology, Sloan School of Managementen_US
dc.description.collectionS.M. Massachusetts Institute of Technology, Department of Mechanical Engineeringen_US
dspace.imported2020-09-03T15:51:42Zen_US
mit.thesis.degreeMasteren_US
mit.thesis.departmentSloanen_US
mit.thesis.departmentMechEen_US


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