1 Ocak 2022 Dergi makalesi Açık Erişim

Dogan, Ilgin; Lokman, Banu; Koksalan, Murat

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  <identifier identifierType="URL">https://aperta.ulakbim.gov.tr/record/236946</identifier>
  <creators>
    <creator>
      <creatorName>Dogan, Ilgin</creatorName>
      <givenName>Ilgin</givenName>
      <familyName>Dogan</familyName>
      <affiliation>Univ Calif Berkeley, Dept Ind Engn &amp; Operat Res, Berkeley, CA 94720 USA</affiliation>
    </creator>
    <creator>
      <creatorName>Lokman, Banu</creatorName>
      <givenName>Banu</givenName>
      <familyName>Lokman</familyName>
      <affiliation>Univ Portsmouth, Portsmouth Business Sch, Ctr Operat Res &amp; Logist, Portsmouth PO1 3DE, Hants, England</affiliation>
    </creator>
    <creator>
      <creatorName>Koksalan, Murat</creatorName>
      <givenName>Murat</givenName>
      <familyName>Koksalan</familyName>
    </creator>
  </creators>
  <titles>
    <title>Representing The Nondominated Set In Multi-Objective Mixed-Integer Programs</title>
  </titles>
  <publisher>Aperta</publisher>
  <publicationYear>2022</publicationYear>
  <dates>
    <date dateType="Issued">2022-01-01</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Journal article</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://aperta.ulakbim.gov.tr/record/236946</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1016/j.ejor.2021.04.005</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="http://www.opendefinition.org/licenses/cc-by">Creative Commons Attribution</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
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  <descriptions>
    <description descriptionType="Abstract">A B S T R A C T In this paper, we consider generating a representative subset of nondominated points at a prespecified precision in multi-objective mixed-integer programs (MOMIPs). The number of nondominated points grows exponentially with problem size and finding all nondominated points is typically hard in MOMIPs. Representing the nondominated set with a small subset of nondominated points is important for a decision maker to get an understanding of the layout of solutions. The shape and density of the nondominated points over the objective space may be critical in obtaining a set of solutions that represent the nondominated set well. We develop an exact algorithm that generates a representative set guaranteeing a prespecified precision. Our experiments on a variety of problems demonstrate that our algorithm outperforms existing approaches in terms of both the cardinality of the representative set and computation times. (c) 2021 Elsevier B.V. All rights reserved.</description>
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