<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-19T06:54:56Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/151494" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/151494</identifier><datestamp>2023-08-01T03:00:54Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>col_1721.1_131023</setSpec></header><metadata><dim:dim xmlns:dim="http://www.dspace.org/xmlns/dspace/dim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.dspace.org/xmlns/dspace/dim http://www.dspace.org/schema/dim.xsd">
   <dim:field mdschema="dc" element="contributor" qualifier="advisor">Roemer, Thomas</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="advisor">Yang, Maria</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author">Fullerton, Avery</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Department of Mechanical Engineering</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Sloan School of Management</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2023-07-31T19:44:12Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2023-07-31T19:44:12Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued">2023-06</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="submitted">2023-07-14T19:57:21.718Z</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">https://hdl.handle.net/1721.1/151494</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract">Ship-pack optimization is a crucial tool for companies to reduce operations cost in their distribution system. Cost elements including transportation costs between manufacturing and distribution, transportation costs between distribution and customer, distribution center labor costs, and distribution box costs are all influenced by the ship-pack size from manufacturing to distribution. Companies that control their distribution channels want to be sure to minimize the amount of repacking that occurs between manufacturing and distribution to the customers. “Eachorders” occur when a company must fulfill an order outside of the ship-pack quantity sent from manufacturing. These “each-orders” incur more distribution handling costs, customer complaints, and more costly freight terms, thereby carrying a high “cost-to-fulfill” number relative to the amount of product sold to customers. This thesis explores two ways to reduce operational costs through adjusting ship-pack delivery. The first is an optimization to change the ship-pack quantity, which results in a savings of around 5% of operational costs annually. The second is an optimization of customer ordering behavior, which results in a savings of around 9% of operational costs annually.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree">S.M.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree">M.B.A.</dim:field>
   <dim:field mdschema="dc" element="publisher">Massachusetts Institute of Technology</dim:field>
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   <dim:field mdschema="dc" element="title">Ship-Pack Optimization to Minimize Fulfillment Costs from Manufacturing to Customer</dim:field>
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   <dim:field mdschema="thesis" element="degree" qualifier="name">Master of Science in Mechanical Engineering</dim:field>
   <dim:field mdschema="thesis" element="degree" qualifier="name">Master of Business Administration</dim:field>
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   	&lt;Title>Ship-Pack Optimization to Minimize Fulfillment Costs from Manufacturing to Customer&lt;/Title>
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   	&lt;PublicationDate>2023-06&lt;/PublicationDate>
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        	&lt;DisplayName>Fullerton, Avery&lt;/DisplayName>
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            &lt;DisplayName>Massachusetts Institute of Technology&lt;/DisplayName>
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   	&lt;Abstract>Ship-pack optimization is a crucial tool for companies to reduce operations cost in their distribution system. Cost elements including transportation costs between manufacturing and distribution, transportation costs between distribution and customer, distribution center labor costs, and distribution box costs are all influenced by the ship-pack size from manufacturing to distribution. Companies that control their distribution channels want to be sure to minimize the amount of repacking that occurs between manufacturing and distribution to the customers. “Eachorders” occur when a company must fulfill an order outside of the ship-pack quantity sent from manufacturing. These “each-orders” incur more distribution handling costs, customer complaints, and more costly freight terms, thereby carrying a high “cost-to-fulfill” number relative to the amount of product sold to customers. This thesis explores two ways to reduce operational costs through adjusting ship-pack delivery. The first is an optimization to change the ship-pack quantity, which results in a savings of around 5% of operational costs annually. The second is an optimization of customer ordering behavior, which results in a savings of around 9% of operational costs annually.&lt;/Abstract>
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