<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>5347</id>
    <completedYear>2015</completedYear>
    <publishedYear>2015</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2015-01-22</completedDate>
    <publishedDate>2015-01-22</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">G-RIPS 2014 RailLab - Towards robust rolling stock rotations</title>
    <abstract language="eng">The Graduate-Level Research in Industrial Projects (G-RIPS) Program provides an &#13;
opportunity for high-achieving graduate-level students to work in teams on a &#13;
real-world research project proposed by a sponsor from industry or the public &#13;
sector. Each G-RIPS team consists of four international students (two from &#13;
the US and two from European universities), an academic mentor, and an industrial sponsor. &#13;
&#13;
This is the report of the Rail-Lab project on the definition and integration of &#13;
robustness aspects into optimizing rolling stock schedules. In general, there is&#13;
a trade-off for complex systems between robustness and efficiency. The ambitious &#13;
goal was to explore this trade-off by implementing numerical simulations and &#13;
developing analytic models. &#13;
&#13;
In rolling stock planning a very large set of industrial railway requirements, &#13;
such as vehicle composition, maintenance constraints, infrastructure capacity, &#13;
and regularity aspects, have to be considered in an integrated model. General &#13;
hypergraphs provide the modeling power to tackle those requirements. &#13;
Furthermore, integer programming approaches are able to produce high quality &#13;
solutions for the deterministic problem.&#13;
&#13;
When stochastic time delays are considered, the mathematical programming problem &#13;
is much more complex and presents additional challenges. Thus, we started with a &#13;
basic variant of the deterministic case, i.e., we are only considering &#13;
hypergraphs representing vehicle composition and regularity.  &#13;
We transfered solution approaches for robust optimization&#13;
from the airline industry to the setting of railways and attained a &#13;
reasonable measure of robustness. Finally, we present and discuss different &#13;
methods to optimize this robustness measure.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-53475</identifier>
    <note>ZIB-Report 14-34</note>
    <author>Charles Brett</author>
    <submitter>Thomas Schlechte</submitter>
    <author>Rebecca Hoberg</author>
    <author>Meritxell Pacheco</author>
    <author>Kyle Smith</author>
    <author>Ralf Borndörfer</author>
    <author>Ricardo Euler</author>
    <author>Gerwin Gamrath</author>
    <author>Boris Grimm</author>
    <author>Olga Heismann</author>
    <author>Markus Reuther</author>
    <author>Thomas Schlechte</author>
    <author>Alexander Tesch</author>
    <series>
      <title>ZIB-Report</title>
      <number>14-34</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>robust optimization, rolling stock planning</value>
    </subject>
    <collection role="msc" number="90-XX">OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="borndoerfer">Borndörfer, Ralf</collection>
    <collection role="persons" number="euler">Euler, Ricardo</collection>
    <collection role="persons" number="grimm">Grimm, Boris</collection>
    <collection role="persons" number="schlechte">Schlechte, Thomas</collection>
    <collection role="projects" number="MODAL-RailLab">MODAL-RailLab</collection>
    <collection role="persons" number="tesch">Tesch, Alexander</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/5347/ZR-14-34.pdf</file>
  </doc>
  <doc>
    <id>6033</id>
    <completedYear/>
    <publishedYear>2016</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>13</pageLast>
    <pageNumber>13</pageNumber>
    <edition/>
    <issue/>
    <volume>54</volume>
    <type>conferenceobject</type>
    <publisherName>Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik</publisherName>
    <publisherPlace>Dagstuhl, Germany</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">The Maximum Flow Problem for Oriented Flows</title>
    <abstract language="eng">In several applications of network flows, additional constraints have to be considered. In this paper, we study flows, where the flow particles have an orientation. For example, cargo containers with doors only on one side and train coaches with 1st and 2nd class compartments have such an orientation. If the end position has a mandatory orientation, not every path from source to sink is feasible for routing or additional transposition maneuvers have to be made. As a result, a source-sink path may visit a certain vertex several times. We describe structural properties of optimal solutions, determine the computational complexity, and present an approach for approximating such flows.</abstract>
    <parentTitle language="eng">16th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2016)</parentTitle>
    <identifier type="doi">10.4230/OASIcs.ATMOS.2016.7</identifier>
    <identifier type="urn">urn:nbn:de:0030-drops-65318</identifier>
    <identifier type="url">http://drops.dagstuhl.de/opus/volltexte/2016/6531</identifier>
    <identifier type="issn">2190-6807</identifier>
    <identifier type="isbn">978-3-95977-021-7</identifier>
    <note>Keywords: network flow with orientation, graph expansion, approximation, container logistics, train routing</note>
    <enrichment key="Series">OpenAccess Series in Informatics (OASIcs)</enrichment>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="SubmissionStatus">epub ahead of print</enrichment>
    <author>Stanley Schade</author>
    <submitter>Stanley Schade</submitter>
    <editor>Marc Goerigk</editor>
    <author>Martin Strehler</author>
    <editor>Renato Werneck</editor>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="institutes" number="traffic">Mathematics of Transportation and Logistics</collection>
    <collection role="projects" number="MODAL-RailLab">MODAL-RailLab</collection>
    <collection role="persons" number="schade">Schade, Stanley</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>6339</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>2017-11-04</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Pattern Detection For Large-Scale Railway Timetables</title>
    <abstract language="eng">We consider railway timetables of our industrial partner DB Fernverkehr AG that operates the ICE high speed trains in the long-distance passenger railway network of Germany. Such a timetable covers a whole year with 364 days and, typically, includes more than 45,000 trips. A rolling stock rotation plan is not created for the whole timetable at once. Instead the timetable is divided into regular invariant sections and irregular deviations (e.g. for public holidays). A separate rotation plan with a weekly period can then be provided for each of the different sections of the timetable. We present an algorithmic approach to automatically recognize these sections. Together with the supplementing visualisation of the timetable this method has shown to be very relevant for our industrial partner.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-63390</identifier>
    <enrichment key="SourceTitle">Appeared in: Proceedings of the IAROR conference RailLille 2017</enrichment>
    <author>Stanley Schade</author>
    <submitter>Stanley Schade</submitter>
    <author>Ralf Borndörfer</author>
    <author>Matthias Breuer</author>
    <author>Boris Grimm</author>
    <author>Markus Reuther</author>
    <author>Thomas Schlechte</author>
    <author>Patrick Siebeneicher</author>
    <series>
      <title>ZIB-Report</title>
      <number>17-17</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>railway timetables</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>visualization</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>pattern detection</value>
    </subject>
    <collection role="msc" number="90-XX">OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="borndoerfer">Borndörfer, Ralf</collection>
    <collection role="persons" number="grimm">Grimm, Boris</collection>
    <collection role="persons" number="schlechte">Schlechte, Thomas</collection>
    <collection role="projects" number="MODAL-RailLab">MODAL-RailLab</collection>
    <collection role="persons" number="schade">Schade, Stanley</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/6339/ZR-17-17.pdf</file>
  </doc>
  <doc>
    <id>5642</id>
    <completedYear>2015</completedYear>
    <publishedYear>2015</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2015-10-29</completedDate>
    <publishedDate>2015-10-29</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Rolling Stock Rotation Optimization in Days of Strike: An Automated Approach for Creating an Alternative Timetable</title>
    <abstract language="eng">The operation of a railway network as large as Deutsche Bahn's Intercity Express (ICE) hinges on a number of factors, such as the availability of personnel and the assignment of physical vehicles to a timetable schedule, a problem known as the rolling stock rotation problem (RSRP).  In this paper, we consider the problem of creating an alternative timetable in the case that there is a long-term disruption, such as a strike, and the effects that this alternative timetable has on the resulting vehicle rotation plan.  We define a priority measure via the Analytic Hierarchy Process (AHP) to determine the importance of each trip in the timetable and therefore which trips to cancel or retain.  We then compare our results with those of a limited timetable manually designed by Deutsche Bahn  (DB). We find that while our timetable results in a more expensive rotation plan, its flexibility lends itself to a number of simple improvements.  Furthermore, our priority measure has the potential to be integrated into the rolling stock rotation optimization process, in particular, the Rotation Optimizer for Railways (ROTOR) software, via the cost function.  Ultimately, our method provides the foundation for an automated way of creating a new timetable quickly, and potentially in conjunction with a new rotation plan, in the case of a limited scenario.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-56425</identifier>
    <enrichment key="PeerReviewed">no</enrichment>
    <author>Sepideh Ahmadi</author>
    <submitter>Stanley Schade</submitter>
    <author>Sascha F. Gritzbach</author>
    <author>Kathryn Lund-Nguyen</author>
    <author>Devita McCullough-Amal</author>
    <series>
      <title>ZIB-Report</title>
      <number>15-52</number>
    </series>
    <collection role="msc" number="90-XX">OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="projects" number="MODAL-RailLab">MODAL-RailLab</collection>
    <collection role="persons" number="schade">Schade, Stanley</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/5642/ZR_15-52.pdf</file>
  </doc>
</export-example>
