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  <doc>
    <id>4346</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
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    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2014-01-26</completedDate>
    <publishedDate>2013-02-27</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Robust Optimization under Multi-band Uncertainty - Part I: Theory</title>
    <abstract language="eng">The classical single-band uncertainty model introduced by Bertsimas and Sim has represented a breakthrough in the development of tractable robust counterparts of Linear Programs. However, adopting a single deviation band may be too limitative in practice: in&#13;
many real-world problems, observed deviations indeed present asymmetric distributions over asymmetric ranges, so that getting a higher modeling resolution by partitioning the band into multiple sub-bands is advisable.&#13;
The critical aim of our work is to close the knowledge gap on the adoption of multi-band uncertainty in Robust Optimization: a general definition and intensive theoretical study of a multi-band model are actually still missing. Our new developments have been also strongly inspired and encouraged by our industrial partners, interested in getting a better modeling of arbitrary shaped distributions, built on historical data about the uncertainty affecting the considered real-world problems.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-43469</identifier>
    <note>Submitted for publication in 2012. Preprint also available in Optimization Online (13-01-3748) and arXiv (1301.2734)</note>
    <author>Christina Büsing</author>
    <submitter>Fabio D'Andreagiovanni</submitter>
    <author>Fabio D'Andreagiovanni</author>
    <series>
      <title>ZIB-Report</title>
      <number>13-10</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Robust Optimization, Multiband Uncertainty, Compact Robust Counterpart, Cutting Planes, Probabilistic Bound</value>
    </subject>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="institutes" number="tele">Mathematics of Telecommunication</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/4346/ZR-13-10_MultibandPartI.pdf</file>
  </doc>
  <doc>
    <id>4409</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2014-02-12</completedDate>
    <publishedDate>2013-12-30</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">0-1 Multiband Robust Optimization</title>
    <abstract language="eng">We provide an overview of new theoretical results that we obtained while further investigating multiband robust optimization, a new model for robust optimization that we recently proposed to tackle uncertainty in mixed-integer linear programming. This new model extends and refines the classical Gamma-robustness model of Bertsimas and Sim and is particularly useful in the common case of arbitrary asymmetric distributions of the uncertainty. Here, we focus on uncertain 0-1 programs and we analyze their robust counterparts when the uncertainty is represented through a multiband set. Our investigations were inspired by the needs of our industrial partners in the research project ROBUKOM.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-44093</identifier>
    <enrichment key="SourceTitle">To appear in: Operations Research Proceedings 2013 - Selected Papers of the International Annual Conference of the German Operations Research Society (GOR), Erasmus University Rotterdam, The Netherlands, September 3-6, 2013, Springer, Heidelberg</enrichment>
    <author>Christina Büsing</author>
    <submitter>Fabio D'Andreagiovanni</submitter>
    <author>Fabio D'Andreagiovanni</author>
    <author>Annie Raymond</author>
    <series>
      <title>ZIB-Report</title>
      <number>13-77</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Combinatorial Optimization, Robust Optimization, Multiband Robustness, Network Design</value>
    </subject>
    <collection role="msc" number="68-XX">COMPUTER SCIENCE (For papers involving machine computations and programs in a specific mathematical area, see Section -04 in that area)</collection>
    <collection role="msc" number="90-XX">OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="institutes" number="tele">Mathematics of Telecommunication</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/4409/ZR-13-77_01MultibandRobustOptimizationGOR2013.pdf</file>
  </doc>
  <doc>
    <id>4264</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2013-10-03</completedDate>
    <publishedDate>2013-10-03</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">A new theoretical framework for Robust Optimization under multi-band uncertainty</title>
    <abstract language="eng">We provide an overview of our main results about studying Linear Programming Problems whose coefficient matrix is subject to uncertainty and the uncertainty is modeled through a multi-band set. Such an uncertainty set generalizes the classical one proposed by Bertsimas and Sim and is particularly suitable in the common case of arbitrary non-symmetric distributions of the parameters. Our investigations were inspired by practical needs of our industrial partner in ongoing projects with focus on the design of robust telecommunications networks.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-42644</identifier>
    <identifier type="url">http://www.springer.com/business+%26+management/operations+research/book/978-3-319-00794-6</identifier>
    <identifier type="doi">10.1007/978-3-319-00795-3_17</identifier>
    <enrichment key="SourceTitle">To appear in Operations Research Proceedings 2012 - Selected Papers of the International Annual Conference of the German Operations Research Society (GOR), Leibniz University of Hannover, Germany, September 5-7, 2012, Helber, S. et al. (Eds.),  Springer, Heidelberg.</enrichment>
    <author>Christina Büsing</author>
    <submitter>Fabio D'Andreagiovanni</submitter>
    <author>Fabio D'Andreagiovanni</author>
    <series>
      <title>ZIB-Report</title>
      <number>13-61</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Robust Optimization, Uncertainty Set, Multiband Robustness, Network Design</value>
    </subject>
    <collection role="msc" number="68-XX">COMPUTER SCIENCE (For papers involving machine computations and programs in a specific mathematical area, see Section -04 in that area)</collection>
    <collection role="msc" number="90-XX">OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="institutes" number="tele">Mathematics of Telecommunication</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/4264/ZR-13-61.pdf</file>
  </doc>
  <doc>
    <id>4255</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2013-09-25</completedDate>
    <publishedDate>2013-09-25</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Network Planning under Demand Uncertainty with Robust Optimization</title>
    <abstract language="eng">The planning of a communication network is inevitably depending on the quality of both the planning tool and the demand forecast used. In this article, we show exemplarily how the emerging area of Robust Optimization can advance the network planning by a more accurate mathematical description of the demand uncertainty. After a general introduction of the concept and its application to a basic network design problem, we present two applications: multi-layer and mixed-line-rate network design. We conclude with a discussion of extensions of the robustness concept to increase the accuracy of handling uncertainties.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-42557</identifier>
    <identifier type="doi">10.1109/MCOM.2014.6736760</identifier>
    <enrichment key="SourceTitle">Accepted for publication in IEEE Communications Magazine, special issue Advances in Network Planning, on September 8th 2013</enrichment>
    <author>Thomas Bauschert</author>
    <submitter>Fabio D'Andreagiovanni</submitter>
    <author>Christina Büsing</author>
    <author>Fabio D'Andreagiovanni</author>
    <author>Arie M.C.A. Koster</author>
    <author>Manuel Kutschka</author>
    <author>Uwe Steglich</author>
    <series>
      <title>ZIB-Report</title>
      <number>13-59</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Network Design, Demand Uncertainty, Robust Optimization, Telecommunications</value>
    </subject>
    <collection role="msc" number="68-XX">COMPUTER SCIENCE (For papers involving machine computations and programs in a specific mathematical area, see Section -04 in that area)</collection>
    <collection role="msc" number="90-XX">OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="institutes" number="tele">Mathematics of Telecommunication</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/4255/ZR-13-59.pdf</file>
  </doc>
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