<?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>2026-09-19T00:42:46Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/122255" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/122255</identifier><datestamp>2026-06-06T01:04:14Z</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">Nima Kazemi.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">lyer Nurani, Vishwanathan Parameshwaran.</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" lang="en_US">Massachusetts Institute of Technology. Supply Chain Management Program</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2019-09-17T19:50:56Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2019-09-17T19:50:56Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2019</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2019</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">https://hdl.handle.net/1721.1/122255</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">1119538858</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, 2019</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 52-53).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">While festivals bring a reason to cheer for everyone, businesses dealing with a spike in demand for perishables may have to live with the misery of lost sales and/or expired items. In the case of the dairy industry that deals with liquid milk, both raw material, and finished goods are perishable, which implies that merely stockpiling inventory of either item, without paying attention to potential inventory losses, cannot be an optimal strategy. In developing countries, the supplier base for perishables like milk, fruits, vegetables, flowers, etc. mostly comprise of small farmers instead of corporate/professional agencies, thus leading to supply variability. During special occasions like festivals, as individuals set aside more of the raw material for their own consumption, we encounter a reduction in supply. Around the same time, we notice a spike in customer demand, leading to a demand-supply mismatch. Companies dealing with perishables need an analytical approach to manage this.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">In this thesis, we present a framework to address this problem of intermittent demand-supply mismatch using a 3-stage stochastic optimization model. We decide on the sourcing targets, the production plans based on supply realized, and finally, the dispatch plan based on orders received. As a case study, we analyze the operations and data from a private dairy company in eastern India, to understand the research problem and the applicability of the resulting model. We notice the impact of demand spikes and supply reduction in two areas: we increase supply targets in the periods preceding the demand spike; and we increase supply targets in periods when supply is expected to decrease, while demand is as usual. When there are multiple festival days within the time series, the compounding of impact depends on the sequencing of the events.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">Finally, when we introduce the realistic constraint that the supply target needs to be constant throughout the time series, we see a degradation in the profitability, as we need to tradeoff between lost sales and wasted products. While the focus of this case study is the dairy industry, the conclusions from this research are broadly applicable to other industries dealing with perishables.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Vishwanathan Parameshwaran lyer Nurani.</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="description" qualifier="collection" lang="en_US">M.Eng.inSupplyChainManagement Massachusetts Institute of Technology, Supply Chain Management Program</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">66 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">Supply Chain Management Program.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">Optimal inventory model for managing demand-supply mismatches for perishables with stochastic supply</dim:field>
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   <dim:field mdschema="mit" element="thesis" qualifier="degree" lang="en_US">Master</dim:field>
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   	&lt;Title>Optimal inventory model for managing demand-supply mismatches for perishables with stochastic supply&lt;/Title>
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   	&lt;PublicationDate>2019&lt;/PublicationDate>
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        	&lt;DisplayName>lyer Nurani, Vishwanathan Parameshwaran.&lt;/DisplayName>
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    &lt;Keyword>Supply Chain Management Program.&lt;/Keyword>
   	&lt;Abstract>While festivals bring a reason to cheer for everyone, businesses dealing with a spike in demand for perishables may have to live with the misery of lost sales and/or expired items. In the case of the dairy industry that deals with liquid milk, both raw material, and finished goods are perishable, which implies that merely stockpiling inventory of either item, without paying attention to potential inventory losses, cannot be an optimal strategy. In developing countries, the supplier base for perishables like milk, fruits, vegetables, flowers, etc. mostly comprise of small farmers instead of corporate/professional agencies, thus leading to supply variability. During special occasions like festivals, as individuals set aside more of the raw material for their own consumption, we encounter a reduction in supply. Around the same time, we notice a spike in customer demand, leading to a demand-supply mismatch. Companies dealing with perishables need an analytical approach to manage this.&lt;/Abstract>
   	&lt;Abstract>In this thesis, we present a framework to address this problem of intermittent demand-supply mismatch using a 3-stage stochastic optimization model. We decide on the sourcing targets, the production plans based on supply realized, and finally, the dispatch plan based on orders received. As a case study, we analyze the operations and data from a private dairy company in eastern India, to understand the research problem and the applicability of the resulting model. We notice the impact of demand spikes and supply reduction in two areas: we increase supply targets in the periods preceding the demand spike; and we increase supply targets in periods when supply is expected to decrease, while demand is as usual. When there are multiple festival days within the time series, the compounding of impact depends on the sequencing of the events.&lt;/Abstract>
   	&lt;Abstract>Finally, when we introduce the realistic constraint that the supply target needs to be constant throughout the time series, we see a degradation in the profitability, as we need to tradeoff between lost sales and wasted products. While the focus of this case study is the dairy industry, the conclusions from this research are broadly applicable to other industries dealing with perishables.&lt;/Abstract>
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