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  <doc>
    <id>366</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>1998-09-04</completedDate>
    <publishedDate>1998-09-04</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Recursive Direct Algorithms for Multistage Stochastic Programs in Financial Engineering</title>
    <abstract language="eng">Multistage stochastic programs can be seen as discrete optimal control problems with a characteristic dynamic structure induced by the scenario tree. To exploit that structure, we propose a highly efficient dynamic programming recursion for the computationally intensive task of KKT systems solution within an interior point method. Test runs on a multistage portfolio selection problem demonstrate the performance of the algorithm.</abstract>
    <identifier type="serial">SC-98-23</identifier>
    <identifier type="opus3-id">367</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-3661</identifier>
    <enrichment key="SourceTitle">Appeared in: P. Kall, H.J. Lüthi (eds.). Operations Research 1998. Sel. Papers of the International Conference on Operations Research, Zürich, 1998, pp. 241-250, Springer, 1999</enrichment>
    <author>Marc Steinbach</author>
    <series>
      <title>ZIB-Report</title>
      <number>SC-98-23</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>multistage stochastic programs</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>discrete dynamics</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>tree-sparse QP</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>KKT recursion</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>finance</value>
    </subject>
    <collection role="ddc" number="000">Informatik, Informationswissenschaft, allgemeine Werke</collection>
    <collection role="msc" number="65F05">Direct methods for linear systems and matrix inversion</collection>
    <collection role="msc" number="65F50">Sparse matrices</collection>
    <collection role="msc" number="90C06">Large-scale problems</collection>
    <collection role="msc" number="90C15">Stochastic programming</collection>
    <collection role="institutes" number="">ZIB Allgemein</collection>
    <collection role="projects" number="OPTINVEST">OPTINVEST</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/366/SC-98-23.ps</file>
    <file>https://opus4.kobv.de/opus4-zib/files/366/SC-98-23.pdf</file>
  </doc>
  <doc>
    <id>370</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>1998-10-30</completedDate>
    <publishedDate>1998-10-30</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Recursive Direct Optimization and Successive Refinement in Multistage Stochastic Programs</title>
    <abstract language="eng">The paper presents a new algorithmic approach for multistage stochastic programs which are seen as discrete optimal control problems with a characteristic dynamic structure induced by the scenario tree. To exploit that structure, we propose a highly efficient dynamic programming recursion for the computationally intensive task of KKT systems solution within a primal-dual interior point method. Convergence is drastically enhanced by a successive refinement technique providing both primal and dual initial estimates. Test runs on a multistage portfolio selection problem demonstrate the performance of the method.</abstract>
    <identifier type="serial">SC-98-27</identifier>
    <identifier type="opus3-id">371</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-3706</identifier>
    <author>Marc Steinbach</author>
    <series>
      <title>ZIB-Report</title>
      <number>SC-98-27</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Multistage stochastic programs</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>discrete dynamics</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>tree-sparse QP</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>KKT recursion</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>successive refinement</value>
    </subject>
    <collection role="ddc" number="000">Informatik, Informationswissenschaft, allgemeine Werke</collection>
    <collection role="msc" number="65F50">Sparse matrices</collection>
    <collection role="msc" number="90C06">Large-scale problems</collection>
    <collection role="msc" number="90C15">Stochastic programming</collection>
    <collection role="institutes" number="">ZIB Allgemein</collection>
    <collection role="projects" number="OPTINVEST">OPTINVEST</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/370/SC-98-27.ps</file>
    <file>https://opus4.kobv.de/opus4-zib/files/370/SC-98-27.pdf</file>
  </doc>
  <doc>
    <id>418</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>1999-08-20</completedDate>
    <publishedDate>1999-08-20</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Markowitz Revisited: Single-Period and Multi-Period Mean-Variance Models</title>
    <abstract language="eng">Mean-variance portfolio analysis provided the first quantitative treatment of the tradeoff between profit and risk. We investigate in detail the interplay between objective and constraints in a number of single-period variants, including semi-variance models. Particular emphasis is laid on avoiding the penalization of overperformance. The results are then used as building blocks in the development and theoretical analysis of multi-period models based on scenario trees. A key property is the possibility to remove surplus money in future decisions, yielding approximate downside risk minimization.</abstract>
    <identifier type="serial">SC-99-30</identifier>
    <identifier type="opus3-id">419</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-4183</identifier>
    <enrichment key="SourceTitle">Appeared in: SIAM Review 43(1), 31-85 (2001)</enrichment>
    <author>Marc Steinbach</author>
    <series>
      <title>ZIB-Report</title>
      <number>SC-99-30</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>mean-variance analysis</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>downside risk</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>multi-period model</value>
    </subject>
    <collection role="ddc" number="000">Informatik, Informationswissenschaft, allgemeine Werke</collection>
    <collection role="msc" number="90C15">Stochastic programming</collection>
    <collection role="msc" number="90C20">Quadratic programming</collection>
    <collection role="institutes" number="">ZIB Allgemein</collection>
    <collection role="projects" number="OPTINVEST">OPTINVEST</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/418/SC-99-30.ps</file>
    <file>https://opus4.kobv.de/opus4-zib/files/418/SC-99-30.pdf</file>
  </doc>
  <doc>
    <id>795</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2004-06-02</completedDate>
    <publishedDate>2004-06-02</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Robust Process Control by Dynamic Stochastic Programming</title>
    <abstract language="eng">Unnecessarily conservative behavior of standard process control techniques can be avoided by stochastic programming models when the distribution of random disturbances is known. In an earlier study we have investigated such an approach for tank level constraints of a distillation process. Here we address techniques that have accelerated the numerical solution of the large and expensive stochastic programs by a factor of six, and then present a refined optimization model for the same application.</abstract>
    <identifier type="serial">04-20</identifier>
    <identifier type="opus3-id">796</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-7959</identifier>
    <enrichment key="SourceTitle">Appeared in : Proc. Appl. Math. Mech. (4)1, (2004) 11-14</enrichment>
    <author>Marc Steinbach</author>
    <series>
      <title>ZIB-Report</title>
      <number>04-20</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Process control</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>random disturbance</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>multistage stochastic program</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>relatively complete recourse</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>tree-sparse NLP</value>
    </subject>
    <collection role="ddc" number="000">Informatik, Informationswissenschaft, allgemeine Werke</collection>
    <collection role="msc" number="90C06">Large-scale problems</collection>
    <collection role="msc" number="90C15">Stochastic programming</collection>
    <collection role="msc" number="93C15">Systems governed by ordinary differential equations [See also 34H05]</collection>
    <collection role="msc" number="93C95">Applications</collection>
    <collection role="institutes" number="">ZIB Allgemein</collection>
    <collection role="projects" number="StochProcCtrl">StochProcCtrl</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/795/ZR-04-20.ps</file>
    <file>https://opus4.kobv.de/opus4-zib/files/795/ZR-04-20.pdf</file>
  </doc>
  <doc>
    <id>583</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2000-05-03</completedDate>
    <publishedDate>2000-05-03</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Hierarchical Sparsity in Multistage Convex Stochastic Programs</title>
    <abstract language="eng">Interior point methods for multistage stochastic programs involve KKT systems with a characteristic global block structure induced by dynamic equations on the scenario tree. We generalize the recursive solution algorithm proposed in an earlier paper so that its linear complexity extends to a refined tree-sparse KKT structure. Then we analyze how the block operations can be specialized to take advantage of problem-specific sparse substructures. Savings of memory and operations for a financial engineering application are discussed in detail.</abstract>
    <identifier type="serial">00-15</identifier>
    <identifier type="opus3-id">584</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-5837</identifier>
    <enrichment key="SourceTitle">Appeared in: Stochastic Optimization. Algorithms and Applications, S. P. Uryasev, P. M. Pardalos, Applied Optimization, Vol. 54, Kluwer Academic Publishers, 2001, pp. 385-410</enrichment>
    <author>Marc Steinbach</author>
    <series>
      <title>ZIB-Report</title>
      <number>00-15</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Multistage Stochastic Programs</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Hierarchical KKT Sparsity</value>
    </subject>
    <collection role="ddc" number="000">Informatik, Informationswissenschaft, allgemeine Werke</collection>
    <collection role="msc" number="90C15">Stochastic programming</collection>
    <collection role="institutes" number="">ZIB Allgemein</collection>
    <collection role="projects" number="OPTINVEST">OPTINVEST</collection>
    <collection role="projects" number="StochProcCtrl">StochProcCtrl</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/583/ZR-00-15.ps</file>
    <file>https://opus4.kobv.de/opus4-zib/files/583/ZR-00-15.pdf</file>
  </doc>
  <doc>
    <id>630</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2001-03-26</completedDate>
    <publishedDate>2001-03-26</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Stochastic Optimization for Operating Chemical Processes Under Uncertainty</title>
    <abstract language="eng">Mathematical optimization techniques are on their way to becoming a standard tool in chemical process engineering. While such approaches are usually based on deterministic models, uncertainties such as external disturbances play a significant role in many real-life applications. The present article gives an introduction to practical issues of process operation and to basic mathematical concepts required for the explicit treatment of uncertainties by stochastic optimization.</abstract>
    <identifier type="serial">01-04</identifier>
    <identifier type="opus3-id">631</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-6304</identifier>
    <enrichment key="SourceTitle">Appeared in: Online Optimization of Large Scale Systems, M. Grötschel, S. O. Krumke, J. Rambau (eds.) Springer, 2001, pp. 457-478</enrichment>
    <author>Rene Henrion</author>
    <author>Pu Li</author>
    <author>Andris Möller</author>
    <author>Marc Steinbach</author>
    <author>Moritz Wendt</author>
    <author>Günter Wozny</author>
    <series>
      <title>ZIB-Report</title>
      <number>01-04</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Uncertainty</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Chemical Processes</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Multistage Stochastic Programs</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Probabilistic Constraints</value>
    </subject>
    <collection role="ddc" number="000">Informatik, Informationswissenschaft, allgemeine Werke</collection>
    <collection role="msc" number="90C06">Large-scale problems</collection>
    <collection role="msc" number="90C15">Stochastic programming</collection>
    <collection role="msc" number="90C30">Nonlinear programming</collection>
    <collection role="msc" number="92E20">Classical flows, reactions, etc. [See also 80A30, 80A32]</collection>
    <collection role="institutes" number="">ZIB Allgemein</collection>
    <collection role="projects" number="StochProcCtrl">StochProcCtrl</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/630/ZR-01-04.ps</file>
    <file>https://opus4.kobv.de/opus4-zib/files/630/ZR-01-04.pdf</file>
  </doc>
  <doc>
    <id>650</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2001-09-28</completedDate>
    <publishedDate>2001-09-28</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">General Information Constraints in Stochastic Programs</title>
    <abstract language="eng">Scenario tree models of stochastic programs arise naturally under standard nonanticipativity assumptions. We demonstrate how tree-sparse programs cover the general case, with \emph{arbitrary} information constraints. Detailed examples and intuitive interpretations illuminate the basic thoughts behind the abstract but elementary construction.</abstract>
    <identifier type="serial">01-24</identifier>
    <identifier type="opus3-id">651</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-6502</identifier>
    <author>Marc Steinbach</author>
    <series>
      <title>ZIB-Report</title>
      <number>01-24</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>information constraints</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>general nonanticipativity</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>sigma-fields</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>filtrations</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>scenarios</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>stochastic programs</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>tree-sparse programs</value>
    </subject>
    <collection role="ddc" number="000">Informatik, Informationswissenschaft, allgemeine Werke</collection>
    <collection role="msc" number="60G99">None of the above, but in this section</collection>
    <collection role="msc" number="90C15">Stochastic programming</collection>
    <collection role="institutes" number="">ZIB Allgemein</collection>
    <collection role="projects" number="StochProcCtrl">StochProcCtrl</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/650/ZR-01-24.ps</file>
    <file>https://opus4.kobv.de/opus4-zib/files/650/ZR-01-24.pdf</file>
  </doc>
  <doc>
    <id>631</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2001-03-26</completedDate>
    <publishedDate>2001-03-26</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">A Multistage Stochastic Programming Approach in Real-Time Process Control</title>
    <abstract language="eng">Standard model predictive control for real-time operation of industrial production processes may be inefficient in the presence of substantial uncertainties. To avoid overly conservative disturbance corrections while ensuring safe operation, random influences should be taken into account explicitly. We propose a multistage stochastic programming approach within the model predictive control framework and apply it to a distillation process with a feed tank buffering external sources. A preliminary comparison to a probabilistic constraints approach is given and first computational results for the distillation process are presented.</abstract>
    <identifier type="serial">01-05</identifier>
    <identifier type="opus3-id">632</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-6317</identifier>
    <enrichment key="SourceTitle">Appeared in: Online Optimization of Large Scale Systems. M. Grötschel, S. O. Krumke, J. Rambau (eds.) Springer, 2001, pp. 479-498</enrichment>
    <author>Izaskun Garrido</author>
    <author>Marc Steinbach</author>
    <series>
      <title>ZIB-Report</title>
      <number>01-05</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Process Control</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Real-Time Optimization</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Multistage Stochastic Programming</value>
    </subject>
    <collection role="ddc" number="000">Informatik, Informationswissenschaft, allgemeine Werke</collection>
    <collection role="msc" number="90C06">Large-scale problems</collection>
    <collection role="msc" number="90C15">Stochastic programming</collection>
    <collection role="institutes" number="">ZIB Allgemein</collection>
    <collection role="projects" number="StochProcCtrl">StochProcCtrl</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/631/ZR-01-05.ps</file>
    <file>https://opus4.kobv.de/opus4-zib/files/631/ZR-01-05.pdf</file>
  </doc>
  <doc>
    <id>634</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2001-04-09</completedDate>
    <publishedDate>2001-04-09</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Tree-Sparse Convex Programs</title>
    <abstract language="eng">Dynamic stochastic programs are prototypical for optimization problems with an inherent tree structure inducing characteristic sparsity patterns in the KKT systems of interior methods. We propose an integrated modeling and solution approach for such tree-sparse programs. Three closely related natural formulations are theoretically analyzed from a control-theoretic viewpoint and compared to each other. Associated KKT solution algorithms with linear complexity are developed and comparisons to other interior approaches and related problem formulations are discussed.</abstract>
    <identifier type="serial">01-08</identifier>
    <identifier type="opus3-id">635</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-6340</identifier>
    <enrichment key="SourceTitle">Appeared in: Mathematical Methods of Operations Research 56 (2002) 347-376</enrichment>
    <author>Marc Steinbach</author>
    <series>
      <title>ZIB-Report</title>
      <number>01-08</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Convex program</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>tree</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>discrete-time optimal control multistage stochastic program</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>recursive factorization</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>local projection</value>
    </subject>
    <collection role="ddc" number="000">Informatik, Informationswissenschaft, allgemeine Werke</collection>
    <collection role="msc" number="15A23">Factorization of matrices</collection>
    <collection role="msc" number="65F50">Sparse matrices</collection>
    <collection role="msc" number="90C06">Large-scale problems</collection>
    <collection role="msc" number="90C15">Stochastic programming</collection>
    <collection role="msc" number="90C25">Convex programming</collection>
    <collection role="institutes" number="">ZIB Allgemein</collection>
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    <language>eng</language>
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    <edition/>
    <issue/>
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    <completedDate>2011-02-28</completedDate>
    <publishedDate>2011-02-28</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Multistage Stochastic Programming in Strategic Telecommunication Network Planning</title>
    <abstract language="eng">Mobile communication is nowadays taken for granted. Having started&#13;
primarily as a service for speech communication, data service and&#13;
mobile Internet access are now driving the evolution of network&#13;
infrastructure.  Operators are facing the challenge to match the&#13;
demand by continuously expanding and upgrading the network&#13;
infrastructure.  However, the evolution of the customer's demand is uncertain.&#13;
&#13;
We introduce a novel (long-term) network planning approach based on&#13;
multistage stochastic programming, where demand evolution is considered as&#13;
a stochastic process and the network is extended as to maximize the&#13;
expected profit. The approach proves capable of designing large-scale&#13;
realistic UMTS networks with a time-horizon of several years.  Our&#13;
mathematical optimization model, the solution approach, and computational&#13;
results are presented in this paper.</abstract>
    <identifier type="serial">11-06</identifier>
    <identifier type="doi">10.1007/s10287-012-0143-5</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-12232</identifier>
    <enrichment key="SourceTitle">Appeared in: Computational Management Science 9 Issue 3 (2012) pp. 303-321</enrichment>
    <author>Andreas Eisenblätter</author>
    <submitter>-empty- (Opus4 user: )</submitter>
    <author>Jonas Schweiger</author>
    <submitter>Jonas Schweiger</submitter>
    <series>
      <title>ZIB-Report</title>
      <number>11-06</number>
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    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>UMTS</value>
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    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Network Evolution</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Multistage</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Stochastic Programming</value>
    </subject>
    <collection role="msc" number="90B18">Communication networks [See also 68M10, 94A05]</collection>
    <collection role="msc" number="90C15">Stochastic programming</collection>
    <collection role="msc" number="90C90">Applications of mathematical programming</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="schweiger">Schweiger, Jonas</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
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  <doc>
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    <language>eng</language>
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    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation>Zuse-Institut Berlin</creatingCorporation>
    <contributingCorporation>Lufthansa Systems Berlin GmbH</contributingCorporation>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2010-05-31</completedDate>
    <publishedDate>2010-05-31</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Robust Tail Assignment</title>
    <abstract language="eng">We propose an efficient column generation method to minimize the probability of delay propagations along aircraft rotations. In this way, delay resistant schedules can be constructed. Computational results for large-scale real-world problems demonstrate substantial punctuality improvements. The method can be generalized to crew and integrated scheduling problems.</abstract>
    <identifier type="serial">10-08</identifier>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="opus3-id">1231</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-11707</identifier>
    <author>Ralf Borndörfer</author>
    <submitter>unknown unknown</submitter>
    <author>Ivan Dovica</author>
    <author>Ivo Nowak</author>
    <author>Thomas Schickinger</author>
    <series>
      <title>ZIB-Report</title>
      <number>10-08</number>
    </series>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Flugzeugumlaufplanung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>robuste Optimierung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Spaltenerzeugung</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Tail Assignment</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Robust Optimization</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Column Generation</value>
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    <collection role="msc" number="90C10">Integer programming</collection>
    <collection role="msc" number="90C15">Stochastic programming</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="borndoerfer">Borndörfer, Ralf</collection>
    <collection role="projects" number="LHS-rxOPT-tail">LHS-rxOPT-tail</collection>
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    <language>eng</language>
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    <edition/>
    <issue/>
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    <completedDate>--</completedDate>
    <publishedDate>2014-07-21</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Gas network extension planning for multiple demand scenarios</title>
    <abstract language="eng">Today's gas markets demand more flexibility from the network operators which in turn have to invest into their network infrastructure. As these investments are very cost-intensive and long-living, network extensions should not only focus on one bottleneck scenario, but should increase the flexibility to fulfill different demand scenarios. We formulate a model for the network extension problem for multiple demand scenarios and propose a scenario decomposition. We solve MINLP single-scenario sub-problems and obtain valid bounds even without solving them to optimality. Heuristics prove capable of improving the initial solutions substantially. Results of computational experiments are presented.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-51030</identifier>
    <author>Jonas Schweiger</author>
    <submitter>Jonas Schweiger</submitter>
    <series>
      <title>ZIB-Report</title>
      <number>14-29</number>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Gas Network Planning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Scenario Decomposition</value>
    </subject>
    <collection role="msc" number="90Bxx">Operations research and management science</collection>
    <collection role="msc" number="90C15">Stochastic programming</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="schweiger">Schweiger, Jonas</collection>
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