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  <doc>
    <id>7251</id>
    <completedYear/>
    <publishedYear>2018</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>268</volume>
    <type>book</type>
    <publisherName>Springer Verlag</publisherName>
    <publisherPlace/>
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    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
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    <title language="eng">Handbook of Optimization in the Railway Industry</title>
    <abstract language="eng">This book promotes the use of mathematical optimization and operations research methods in rail transportation.  The editors assembled thirteen contributions from leading scholars to present a unified voice, standardize terminology, and assess the state-of-the-art.&#13;
&#13;
There are three main clusters of articles, corresponding to the classical stages of the planning process: strategic, tactical, and operational.  These three clusters are further subdivided into five parts which correspond to the main phases of the railway network planning process: network assessment, capacity planning, timetabling, resource planning, and operational planning.  Individual chapters cover:&#13;
&#13;
Simulation&#13;
&#13;
Capacity Assessment&#13;
&#13;
Network Design&#13;
&#13;
Train Routing&#13;
&#13;
Robust Timetabling&#13;
&#13;
Event Scheduling&#13;
&#13;
Track Allocation&#13;
&#13;
Blocking&#13;
&#13;
Shunting&#13;
&#13;
Rolling Stock&#13;
&#13;
Crew Scheduling&#13;
&#13;
Dispatching&#13;
&#13;
Delay Propagation</abstract>
    <identifier type="isbn">978-3-319-72152-1</identifier>
    <identifier type="doi">10.1007/978-3-319-72153-8</identifier>
    <enrichment key="Series">International Series in Operations Research and Management Science</enrichment>
    <enrichment key="PeerReviewed">yes</enrichment>
    <author>Erwin Abbink</author>
    <submitter>Ralf Borndörfer</submitter>
    <editor>Ralf Borndörfer</editor>
    <author>Andreas Bärmann</author>
    <editor>Torsten Klug</editor>
    <author>Nikola Bešinovic</author>
    <editor>Leonardo Lamorgese</editor>
    <editor>Carlo Mannino</editor>
    <author>Markus Bohlin</author>
    <editor>Markus Reuther</editor>
    <author>Valentina Cacchiani</author>
    <author>Gabrio Caimi</author>
    <editor>Thomas Schlechte</editor>
    <author>Stefano de Fabris</author>
    <author>Twan Dollevoet</author>
    <author>Frank Fischer</author>
    <author>Armin Fügenschuh</author>
    <author>Laura Galli</author>
    <author>Rob M.P. Goverde</author>
    <author>Ronny Hansmann</author>
    <author>Henning Homfeld</author>
    <author>Dennis Huisman</author>
    <author>Marc Johann</author>
    <author>Torsten Klug</author>
    <author>Johanna Törnquist Krasemann</author>
    <author>Leo Kroon</author>
    <author>Leonardo Lamorgese</author>
    <author>Frauke Liers</author>
    <author>Carlo Mannino</author>
    <author>Giorgio Medeossi</author>
    <author>Dario Pacciarelli</author>
    <author>Markus Reuther</author>
    <author>Thomas Schlechte</author>
    <author>Marie Schmidt</author>
    <author>Anita Schöbel</author>
    <author>Hanno Schülldorf</author>
    <author>Anke Stieber</author>
    <author>Sebastian Stiller</author>
    <author>Paolo Toth</author>
    <author>Uwe Zimmermann</author>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="borndoerfer">Borndörfer, Ralf</collection>
    <collection role="persons" number="klug">Klug, Torsten</collection>
    <collection role="persons" number="schlechte">Schlechte, Thomas</collection>
    <collection role="projects" number="ECMath-MI3">ECMath-MI3</collection>
    <collection role="projects" number="KOSMOS">KOSMOS</collection>
    <collection role="projects" number="MATHEON-B15">MATHEON-B15</collection>
    <collection role="projects" number="MODAL-RailLab">MODAL-RailLab</collection>
    <collection role="projects" number="ROTOR">ROTOR</collection>
    <collection role="projects" number="Trassenbörse">Trassenbörse</collection>
    <collection role="projects" number="VS-Rail">VS-Rail</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="persons" number="reuther">Reuther, Markus</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>6122</id>
    <completedYear/>
    <publishedYear>2017</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>196</pageFirst>
    <pageLast>211</pageLast>
    <pageNumber/>
    <edition/>
    <issue>1</issue>
    <volume>74</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
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    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2016-11-29</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Recent success stories on integrated optimization of railway systems</title>
    <abstract language="eng">Planning and operating railway transportation systems is an extremely hard task due to the combinatorial complexity of the underlying discrete optimization problems, the technical intricacies, and the immense size of the problem instances. Because of that, however, mathematical models and optimization techniques can result in large gains for both railway customers and operators, e.g., in terms of cost reductions or service quality improvements. In the last years a large and growing group of researchers in the OR community have devoted their attention to this domain developing mathematical models and optimization approaches to tackle many of the relevant problems in the railway planning process. However, there is still a gap to bridge between theory and practice (e.g. Cacchiani et al., 2014; Borndörfer et al., 2010), with a few notable exceptions. In this paper we address three individual success stories, namely, long-term freight train routing (part I), mid-term rolling stock rotation planning (part II), and real-time train dispatching (part III). In each case, we describe real-life, successful implementations. We will discuss the individual problem setting, survey the optimization literature, and focus on particular aspects addressed by the mathematical models. We demonstrate on concrete applications how mathematical optimization can support railway planning and operations. This gives proof that mathematical optimization can support the planning of railway resources. Thus, mathematical models and optimization can lead to a greater efficiency of railway operations and will serve as a powerful and innovative tool to meet recent challenges of the railway industry.</abstract>
    <parentTitle language="eng">Transportation Research Part C: Emerging Technologies</parentTitle>
    <identifier type="doi">10.1016/j.trc.2016.11.015</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <author>Ralf Borndörfer</author>
    <submitter>Thomas Schlechte</submitter>
    <author>Torsten Klug</author>
    <author>Leonardo Lamorgese</author>
    <author>Carlo Mannino</author>
    <author>Markus Reuther</author>
    <author>Thomas Schlechte</author>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="borndoerfer">Borndörfer, Ralf</collection>
    <collection role="persons" number="klug">Klug, Torsten</collection>
    <collection role="persons" number="schlechte">Schlechte, Thomas</collection>
    <collection role="projects" number="KOSMOS">KOSMOS</collection>
    <collection role="projects" number="MODAL-RailLab">MODAL-RailLab</collection>
    <collection role="projects" number="ROTOR">ROTOR</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="persons" number="reuther">Reuther, Markus</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>5372</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
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    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>2015-02-18</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Recent Success Stories on Optimization of Railway Systems</title>
    <abstract language="eng">Planning and operating railway transportation systems is an extremely&#13;
hard task due to the combinatorial complexity of the underlying discrete&#13;
optimization problems, the technical intricacies, and the immense size of&#13;
the problem instances. Because of that, however, mathematical models&#13;
and optimization techniques can result in large gains for both railway cus-&#13;
tomers and operators, e.g., in terms of cost reductions or service quality&#13;
improvements. In the last years a large and growing group of researchers&#13;
in the OR community have devoted their attention to this domain devel-&#13;
oping mathematical models and optimization approaches to tackle many&#13;
of the relevant problems in the railway planning process. However, there&#13;
is still a gap to bridge between theory and practice, with&#13;
a few notable exceptions. In this paper we address three success stories,&#13;
namely, long-term freight train routing (part I), mid-term rolling stock&#13;
rotation planning (part II), and real-time train dispatching (part III). In&#13;
each case, we describe real-life, successful implementations. We will dis-&#13;
cuss the individual problem setting, survey the optimization literature,&#13;
and focus on particular aspects addressed by the mathematical models.&#13;
We demonstrate on concrete applications how mathematical optimization&#13;
can support railway planning and operations. This gives proof that math-&#13;
ematical optimization can support the planning of rolling stock resources.&#13;
Thus, mathematical models and optimization can lead to a greater effi-&#13;
ciency of railway operations and will serve as a powerful and innovative&#13;
tool to meet recent challenges of the railway industry.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-53726</identifier>
    <enrichment key="SourceTitle">Appeared in: Proceedings of the IAROR conference RailTokyo</enrichment>
    <author>Ralf Borndörfer</author>
    <submitter>Markus Reuther</submitter>
    <author>Torsten Klug</author>
    <author>Leonardo Lamorgese</author>
    <author>Carlo Mannino</author>
    <author>Markus Reuther</author>
    <author>Thomas Schlechte</author>
    <series>
      <title>ZIB-Report</title>
      <number>14-47</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>railway planning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>railway operations</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>capacity optimization</value>
    </subject>
    <collection role="msc" number="90-XX">OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="institutes" number="traffic">Mathematics of Transportation and Logistics</collection>
    <collection role="persons" number="borndoerfer">Borndörfer, Ralf</collection>
    <collection role="persons" number="klug">Klug, Torsten</collection>
    <collection role="persons" number="schlechte">Schlechte, Thomas</collection>
    <collection role="projects" number="KOSMOS">KOSMOS</collection>
    <collection role="projects" number="MODAL-RailLab">MODAL-RailLab</collection>
    <collection role="projects" number="ROTOR">ROTOR</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="persons" number="reuther">Reuther, Markus</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/5372/ZR-14-47.pdf</file>
  </doc>
</export-example>
