<?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>2026-09-19T17:16:02Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/130822" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/130822</identifier><datestamp>2021-07-05T14:03:20Z</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">David Simchi-Levi.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Ledvina, Kirby.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Massachusetts Institute of Technology. Department of Civil and Environmental Engineering.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department" lang="en_US">Massachusetts Institute of Technology. Department of Civil and Environmental Engineering</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2021-05-25T18:21:30Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2021-05-25T18:21:30Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2021</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2021</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">https://hdl.handle.net/1721.1/130822</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">1252627492</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis: S.M., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, February, 2021</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Cataloged from the official PDF of thesis.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (pages 57-58).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">We develop and numerically test a new strategy for the vehicle routing problem with stochastic customer demands. In our proposed approach, drivers are assigned to predetermined delivery routes in which adjacent routes share some customers. This overlapping assignment structure, which is inspired by the open chain design from the field of manufacturing process flexibility, enables drivers to adapt to variable customer demands while still maintaining largely consistent routes. Through an extensive computational study and scenario analysis, we show that relative to a system without customer sharing, such flexible routing strategies partly mitigate the transportation costs of filling unexpected customer demands, and the relative savings grow with the number of customers in the network. We also find that much of the cost savings is gained with just the first customer that is shared between adjacent routes. Thus, the overlapped routing model forms the basis for a practical and efficient strategy to manage costs from demand uncertainty.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Kirby Ledvina.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">S.M.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="collection" lang="en_US">S.M. Massachusetts Institute of Technology, Department of Civil and Environmental Engineering</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">71 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>
   <dim:field mdschema="dc" element="rights" qualifier="uri" lang="en_US">http://dspace.mit.edu/handle/1721.1/7582</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_US">Civil and Environmental Engineering.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">A computational study of flexible routing strategies for the VRP with stochastic demands</dim:field>
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   <dim:field mdschema="mit" element="thesis" qualifier="degree" lang="en_US">Master</dim:field>
   <dim:field mdschema="mit" element="thesis" qualifier="department" lang="en_US">CivEng</dim:field>
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   	&lt;Title>A computational study of flexible routing strategies for the VRP with stochastic demands&lt;/Title>
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   	&lt;PublicationDate>2021&lt;/PublicationDate>
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    &lt;Keyword>Civil and Environmental Engineering.&lt;/Keyword>
   	&lt;Abstract>We develop and numerically test a new strategy for the vehicle routing problem with stochastic customer demands. In our proposed approach, drivers are assigned to predetermined delivery routes in which adjacent routes share some customers. This overlapping assignment structure, which is inspired by the open chain design from the field of manufacturing process flexibility, enables drivers to adapt to variable customer demands while still maintaining largely consistent routes. Through an extensive computational study and scenario analysis, we show that relative to a system without customer sharing, such flexible routing strategies partly mitigate the transportation costs of filling unexpected customer demands, and the relative savings grow with the number of customers in the network. We also find that much of the cost savings is gained with just the first customer that is shared between adjacent routes. Thus, the overlapped routing model forms the basis for a practical and efficient strategy to manage costs from demand uncertainty.&lt;/Abstract>
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