<?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>2026-09-18T21:59:29Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/81102" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/81102</identifier><datestamp>2026-06-06T01:03:58Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>com_1721.1_101402</setSpec><setSpec>col_1721.1_131023</setSpec><setSpec>col_1721.1_101610</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">Jarrod Goentzel and Jason Acimovic.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Nishimura, Kathryn K. (Kathryn Kimie)</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Wang, Jian</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Massachusetts Institute of Technology. Engineering Systems Division.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Engineering Systems Division</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2013-09-24T19:42:58Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2013-09-24T19:42:58Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2013</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2013</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">http://hdl.handle.net/1721.1/81102</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">858278023</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2013.</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 (p. 63-65).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">Since the year 2000, at least 300 disasters occurred annually, catching more than 100 million people unprepared and in need of international assistance every year. The United Nations operates five humanitarian response depots (UNHRDs), stocked with over 1,000 types of humanitarian relief items. In the event of an emergency, the UNHRDs deploy the pre-positioned stocks to meet the initial demand of those people affected. Our thesis evaluates the response capacity of the UNHRDs to a single potential disaster: what percentage of total affected people can be served and in what time period. Developed from a stochastic linear programming model, this two-part index assumes that the depots operate as a network, lead times are proportional to distances from depots, and stockpiles are optimized individually for each relief item. Given a specific level of initial inventory for each item, the model also provides insight into how to distribute relief items throughout the five depots to minimize the expected delivery time. Based on a marginal benefit analysis, each unit of inventory is allocated to a depot to minimize the total expected delivery times to disasters. We describe how the UNHRDs and other humanitarian relief organizations can strategically pre-position limited emergency relief resources to maximize their capacity to respond to disasters.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Kathryn K. Nishimura and Jian Wang.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">M.Eng. in Logistics</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">74 p.</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">M.I.T. theses are protected by 
copyright. They may be viewed from this source for any purpose, but 
reproduction or distribution in any format is prohibited without written 
permission. See provided URL for inquiries about permission.</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">Engineering Systems Division.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">Calculating humanitarian response capacity</dim:field>
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   	&lt;Title>Calculating humanitarian response capacity&lt;/Title>
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   	&lt;PublicationDate>2013&lt;/PublicationDate>
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        	&lt;DisplayName>Nishimura, Kathryn K. (Kathryn Kimie)&lt;/DisplayName>
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        	&lt;DisplayName>Wang, Jian&lt;/DisplayName>
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   	&lt;Abstract>Since the year 2000, at least 300 disasters occurred annually, catching more than 100 million people unprepared and in need of international assistance every year. The United Nations operates five humanitarian response depots (UNHRDs), stocked with over 1,000 types of humanitarian relief items. In the event of an emergency, the UNHRDs deploy the pre-positioned stocks to meet the initial demand of those people affected. Our thesis evaluates the response capacity of the UNHRDs to a single potential disaster: what percentage of total affected people can be served and in what time period. Developed from a stochastic linear programming model, this two-part index assumes that the depots operate as a network, lead times are proportional to distances from depots, and stockpiles are optimized individually for each relief item. Given a specific level of initial inventory for each item, the model also provides insight into how to distribute relief items throughout the five depots to minimize the expected delivery time. Based on a marginal benefit analysis, each unit of inventory is allocated to a depot to minimize the total expected delivery times to disasters. We describe how the UNHRDs and other humanitarian relief organizations can strategically pre-position limited emergency relief resources to maximize their capacity to respond to disasters.&lt;/Abstract>
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