<?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>2026-09-19T23:13:50Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/117930" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/117930</identifier><datestamp>2026-06-06T01:04:11Z</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" lang="en_US">Mohammad Moshref-Javadi and Matthias Winkenbach.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Yoon, Justin J</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Massachusetts Institute of Technology. Supply Chain Management Program.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Supply Chain Management Program</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2018-09-17T15:50:26Z</dim:field>
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   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2018</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2018</dim:field>
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   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">1051223610</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2018.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Cataloged from PDF version of thesis.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (pages 47-49).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">With the increasingly competitive landscape of e-commerce and omni-channel delivery execution, the last mile has emerged as a critical source of opportunity for cost efficiency. Unmanned aerial vehicles (UAVs) have historically been utilized for military applications, but they are quickly gaining traction as a viable option for driving improvements in commercial last-mile operations. Although extensive literature currently exists on vehicle routing problems, research integrating drones as a supplement to these routing problems is scarce. This thesis explores the feasibility of deploying drones to the last mile, by modeling the cost of serving customers with one truck and multiple drones in the context of the traveling salesman problem. The model is constructed with mixed integer linear programming (MILP) optimization and assessed with a sensitivity analysis of several key parameters. We find significant median cost savings over TSP of 30 percent in the base case, and that these effects on savings can diminish to a median 4 percent in the worst case while surging up to 55 percent in the best case.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Justin J. Yoon.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">M.Eng. in Supply Chain Management</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">49 pages</dim:field>
   <dim:field mdschema="dc" element="language" qualifier="iso" lang="en_US">eng</dim:field>
   <dim:field mdschema="dc" element="publisher" lang="en_US">Massachusetts Institute of Technology</dim:field>
   <dim:field mdschema="dc" element="rights" lang="en_US">MIT 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.</dim:field>
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   <dim:field mdschema="dc" element="subject" lang="en_US">Supply Chain Management Program.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">The traveling salesman problem with multiple drones : an optimization model for last-mile delivery</dim:field>
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   	&lt;Title>The traveling salesman problem with multiple drones : an optimization model for last-mile delivery&lt;/Title>
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   	&lt;PublicationDate>2018&lt;/PublicationDate>
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    &lt;Keyword>Supply Chain Management Program.&lt;/Keyword>
   	&lt;Abstract>With the increasingly competitive landscape of e-commerce and omni-channel delivery execution, the last mile has emerged as a critical source of opportunity for cost efficiency. Unmanned aerial vehicles (UAVs) have historically been utilized for military applications, but they are quickly gaining traction as a viable option for driving improvements in commercial last-mile operations. Although extensive literature currently exists on vehicle routing problems, research integrating drones as a supplement to these routing problems is scarce. This thesis explores the feasibility of deploying drones to the last mile, by modeling the cost of serving customers with one truck and multiple drones in the context of the traveling salesman problem. The model is constructed with mixed integer linear programming (MILP) optimization and assessed with a sensitivity analysis of several key parameters. We find significant median cost savings over TSP of 30 percent in the base case, and that these effects on savings can diminish to a median 4 percent in the worst case while surging up to 55 percent in the best case.&lt;/Abstract>
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