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dc.contributor.advisorDavid Simchi-Levi and Nikos Trichakis.en_US
dc.contributor.authorStern, Skyler Evan.en_US
dc.contributor.otherSloan School of Management.en_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Civil and Environmental Engineering.en_US
dc.contributor.otherLeaders for Global Operations Program.en_US
dc.date.accessioned2019-10-11T22:24:49Z
dc.date.available2019-10-11T22:24:49Z
dc.date.copyright2019en_US
dc.date.issued2019en_US
dc.date.issued2019en_US
dc.identifier.urihttps://hdl.handle.net/1721.1/122587
dc.descriptionThesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2019, In conjunction with the Leaders for Global Operations Program at MITen_US
dc.descriptionThesis: S.M., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2019, In conjunction with the Leaders for Global Operations Program at MITen_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 55-56).en_US
dc.description.abstractMaintaining high on-time delivery performance is a key objective for Amazon.com and an expectation from customers. This objective is particularly challenging to achieve during periods of peak demand, when extremely high order volumes must be delivered by the promised date. During these peak periods, managing the availability of two-day delivery promises is critical to preventing the overloading of either fulfillment or transportation capabilities. Delivery promise policy establishes daily deadlines by which orders must be placed to be eligible for a two-day promise. Historically, the policy has been set to align expected outbound shipment volume with available transportation capacity, without a similar level of consideration for fulfillment network order processing capacity.en_US
dc.description.abstractTo help prevent the fulfillment centers from receiving too much work due out too soon, particularly during peak periods, fulfillment network capacity should be more explicitly considered when making promise policy decisions. This paper presents a methodology for using the promise policy to control the rate of new workable demand (NWD) arrival to the fulfillment network during a peak period. Analysis of data from Black Friday 2017 reveals that the promise policy impacts the speed with which ordered items are dispatched to fulfillment centers. This effect is incorporated into an optimization model which seeks to maximize the availability of two-day promises each day while constraining the resulting NWD to a daily limit. The model output is the latest recommended promise policy cutoff time for each day as well as hourly and daily predictions for network-wide NWD. The results of a pilot study conducted during the week of Prime Day 2018 (July 16-20) are presented and discussed.en_US
dc.description.abstractFor this week, the model recommended that two-day delivery promises be cut off of at 18:00 Pacific Time on July 17 to maintain NWD below daily limits, with no cutoff times required for the rest of the week. The hourly and daily NWD predictions achieved a weighted mean absolute percentage error of 8.9% and 7.3% across the week, respectively.en_US
dc.description.statementofresponsibilityby Skyler Evan Stern.en_US
dc.format.extent56 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectSloan School of Management.en_US
dc.subjectCivil and Environmental Engineering.en_US
dc.subjectLeaders for Global Operations Program.en_US
dc.titleOptimization of delivery promise policy to control peak demand on a fulfillment networken_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 Civil and Environmental Engineeringen_US
dc.contributor.departmentLeaders for Global Operations Programen_US
dc.identifier.oclc1119391629en_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 Civil and Environmental Engineeringen_US
dspace.imported2019-10-11T22:24:48Zen_US
mit.thesis.degreeMasteren_US
mit.thesis.departmentSloanen_US
mit.thesis.departmentCivEngen_US


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