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dc.contributor.advisorChris Caplice and Francisco Jauffred.en_US
dc.contributor.authorHuang, Tianshu, M. Eng. Massachusetts Institute of Technologyen_US
dc.contributor.authorSerrano, María Bernardaen_US
dc.contributor.otherMassachusetts Institute of Technology. Supply Chain Management Program.en_US
dc.date.accessioned2017-12-20T18:15:26Z
dc.date.available2017-12-20T18:15:26Z
dc.date.copyright2017en_US
dc.date.issued2017en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/112868
dc.descriptionThesis: M. Eng. in Logistics, Massachusetts Institute of Technology, Supply Chain Management Program, 2017.en_US
dc.descriptionThesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2017.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 48-49).en_US
dc.description.abstractTransportation cost is one of the major costs in supply chain. Companies need to optimize every aspect of the transportation process to reduce the total logistics cost. A key aspect is optimal mode selection to minimize the cost of every lane in a company's transportation network. The traditional approach is to select the mode based on freight cost and average transit time. Besides these two factors, the transit variability associated with each mode choice also impacts the transportation cost in an indirect way. In particular, higher variability of transit time will lead to a higher safety stock level in order to keep up with service level, resulting in higher inventory holding cost. To study the impact of transit time variability, we first generated transit time distribution from data provided by a larger retailer. Then we constructed a total logistics cost equation based on transportation cost, inventory cost that incorporates both average transit time and transit time variability from the transit time distribution. Lastly, we conducted sensitivity analysis using the total logistics cost equation with respect to changes in service level, load value, and volume. Beside mode selection problem, our approach of including cost of variability in total cost calculation can be applied to general problems that deals with uncertainties.en_US
dc.description.statementofresponsibilityby Tianshu Huang and Maria Bernarda Serrano.en_US
dc.format.extent55 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.subjectSupply Chain Management Program.en_US
dc.titleIntermodal variability and optimal mode selectionen_US
dc.typeThesisen_US
dc.description.degreeM. Eng. in Logisticsen_US
dc.description.degreeM. Eng. in Supply Chain Managementen_US
dc.contributor.departmentMassachusetts Institute of Technology. Supply Chain Management Program
dc.identifier.oclc1014335752en_US


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