<?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>2026-09-19T02:01:20Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/98564" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/98564</identifier><datestamp>2022-01-13T07:54:48Z</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">James B. Orlin.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Rhee, Donguk</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Massachusetts Institute of Technology. Operations Research Center.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Operations Research Center</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Sloan School of Management</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2015-09-17T17:42:51Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2015-09-17T17:42:51Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2015</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2015</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">http://hdl.handle.net/1721.1/98564</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">920857251</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis: S.M., Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2015.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">This electronic version was submitted by the student author.  The certified thesis is available in the Institute Archives and Special Collections.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Cataloged from student-submitted PDF version of thesis.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (pages 61-62).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">A fully polynomial time approximation scheme (FPTAS) is an algorithm that returns ... -optimal solution to a maximization problem of size n, which runs in polynomial time in both ... We develop faster FPTASs for several classes of knapsack problems. In this thesis, we will first survey the relevant literature in FPTASs for knapsack problems. We propose the use of floating point arithmetic rather than the use of geometric rounding in order to simplify analysis. Given a knapsack problem that yield an ... -optimal solution for disjoint subsets S and T of decision variables, we show how to attain ... -optimal solution for the knapsack problem for the set ... We use this procedure to speed up the run-time of FPTASs for: 1. The Integer Knapsack Problem, 2. The Unbounded Integer Knapsack Problem, 3. The Multiple-Choice Knapsack Problem, and, 4. The Nonlinear Integer Knapsack Problem, Using addition ideas, we develop a fast fully polynomial time randomized approximation scheme (FPTAS) for the 0-1 Knapsack Problem, which has the run-time of ...</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Donguk Rhee.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">S.M.</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">62 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">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">Operations Research Center.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">Faster fully polynomial approximation schemes for Knapsack problems</dim:field>
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   	&lt;Title>Faster fully polynomial approximation schemes for Knapsack problems&lt;/Title>
   	&lt;Subtitle>Faster FPTASs for Knapsack problems&lt;/Subtitle>
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   	&lt;PublicationDate>2015&lt;/PublicationDate>
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   	&lt;Abstract>A fully polynomial time approximation scheme (FPTAS) is an algorithm that returns ... -optimal solution to a maximization problem of size n, which runs in polynomial time in both ... We develop faster FPTASs for several classes of knapsack problems. In this thesis, we will first survey the relevant literature in FPTASs for knapsack problems. We propose the use of floating point arithmetic rather than the use of geometric rounding in order to simplify analysis. Given a knapsack problem that yield an ... -optimal solution for disjoint subsets S and T of decision variables, we show how to attain ... -optimal solution for the knapsack problem for the set ... We use this procedure to speed up the run-time of FPTASs for: 1. The Integer Knapsack Problem, 2. The Unbounded Integer Knapsack Problem, 3. The Multiple-Choice Knapsack Problem, and, 4. The Nonlinear Integer Knapsack Problem, Using addition ideas, we develop a fast fully polynomial time randomized approximation scheme (FPTAS) for the 0-1 Knapsack Problem, which has the run-time of ...&lt;/Abstract>
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