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  <doc>
    <id>6143</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>2016-12-17</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Optimization of Handouts for Rolling Stock Rotations Visualization</title>
    <abstract language="eng">A railway operator creates (rolling stock) rotations in order to have a precise master plan for the&#13;
operation of a timetable by railway vehicles. A rotation is considered as a cycle that multiply&#13;
traverses a set of operational days while covering trips of the timetable. As it is well known,&#13;
the proper creation of rolling stock rotations by, e.g., optimization algorithms is challenging&#13;
and still a topical research subject. Nevertheless, we study a completely different but strongly&#13;
related question in this paper, i.e.: How to visualize a rotation? For this purpose, we introduce&#13;
a basic handout concept, which directly leads to the visualization, i.e., handout of a rotation. In&#13;
our industrial application at DB Fernverkehr AG, the handout is exactly as important as the&#13;
rotation itself. Moreover, it turns out that also other European railway operators use exactly the&#13;
same methodology (but not terminology). Since a rotation can have many handouts of different&#13;
quality, we show how to compute optimal ones through an integer program (IP) by standard&#13;
software. In addition, a construction as well as an improvement heuristic are presented. Our&#13;
computational results show that the heuristics are a very reliable standalone approach to quickly&#13;
find near-optimal and even optimal handouts. The efficiency of the heuristics is shown via a&#13;
computational comparison to the IP approach.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-61430</identifier>
    <author>Ralf Borndörfer</author>
    <submitter>Thomas Schlechte</submitter>
    <author>Boris Grimm</author>
    <author>Markus Reuther</author>
    <author>Thomas Schlechte</author>
    <series>
      <title>ZIB-Report</title>
      <number>ZR-16-73</number>
    </series>
    <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="grimm">Grimm, Boris</collection>
    <collection role="persons" number="schlechte">Schlechte, Thomas</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/6143/ZR-16-73.pdf</file>
  </doc>
  <doc>
    <id>4770</id>
    <completedYear/>
    <publishedYear>2013</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>50</pageFirst>
    <pageLast>66</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>54</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">A Direct Comparison of Physical Block Occupancy Versus Timed Block Occupancy in Train Timetabling Formulations</title>
    <abstract language="eng">Two fundamental mathematical formulations for railway timetabling&#13;
are compared on a common set of sample problems, representing both&#13;
multiple track high density services in Europe and single track bidirectional&#13;
operations in North America. One formulation, ACP, enforces&#13;
against conflicts by constraining time intervals between trains,&#13;
while the other formulation, RCHF, monitors physical occupation of&#13;
controlled track segments. The results demonstrate that both ACP&#13;
and RCHF return comparable solutions in the aggregate, with some&#13;
significant differences in select instances, and a pattern of significant&#13;
differences in performance and constraint enforcement overall.</abstract>
    <parentTitle language="eng">Transportation Research Part E: Logistics and Transportation Review</parentTitle>
    <identifier type="doi">10.1016/j.tre.2013.04.003</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="PreprintUrn">urn:nbn:de:0297-zib-17946</enrichment>
    <author>Steven Harrod</author>
    <submitter>Gerwin Gamrath</submitter>
    <author>Thomas Schlechte</author>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="institutes" number="traffic">Mathematics of Transportation and Logistics</collection>
    <collection role="persons" number="schlechte">Schlechte, Thomas</collection>
    <collection role="projects" number="KOSMOS">KOSMOS</collection>
    <collection role="projects" number="Trassenbörse">Trassenbörse</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>7429</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>2019-08-07</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">A Three-Phase Heuristic for Cyclic Crew Rostering with Fairness Requirements</title>
    <abstract language="eng">In this paper, we consider the Cyclic Crew Rostering Problem with Fairness Requirements (CCRP-FR). In this problem, attractive cyclic rosters have to be constructed for groups of employees, considering multiple, a priori determined, fairness levels. The attractiveness follows from the structure of the rosters (e.g., sufficient rest times and variation in work), whereas fairness is based on the work allocation  among the different roster groups. We propose a three-phase heuristic for the CCRP-FR, which  combines the strength of column generation techniques with a large-scale neighborhood search algorithm.  The design of the heuristic assures that good solutions for all fairness levels are obtained quickly, and can still be further improved if additional running time is available. We evaluate the performance of the algorithm using real-world data from Netherlands Railways, and show that the heuristic finds close to optimal solutions for many of the considered instances. In particular, we show that the heuristic is able to quickly find major improvements upon the current sequential practice: For most instances, the heuristic is  able to increase the attractiveness  by at least 20% in just a few minutes.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-74297</identifier>
    <author>Thomas Breugem</author>
    <submitter>Thomas Schlechte</submitter>
    <author>Ralf Borndörfer</author>
    <author>Thomas Schlechte</author>
    <author>Christof Schulz</author>
    <series>
      <title>ZIB-Report</title>
      <number>19-43</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Crew Planning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Column Generation</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Variable-Depth Neighborhood Search</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="schlechte">Schlechte, Thomas</collection>
    <collection role="persons" number="schulz">Schulz, Christof</collection>
    <collection role="projects" number="MODAL-RailLab">MODAL-RailLab</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/7429/ZR-19-43.pdf</file>
  </doc>
  <doc>
    <id>7466</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
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    <type>reportzib</type>
    <publisherName/>
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    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>2019-09-11</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Multi-Period Line Planning with Resource Transfers</title>
    <abstract language="eng">Urban transportation systems are subject to a high level of variation and fluctuation in demand over the day. When this variation and fluctuation are observed in both time and space, it is crucial to develop line plans that are responsive to demand. A multi-period line planning approach that considers a changing demand during the planning horizon is proposed. If such systems are also subject to limitations of resources, a dynamic transfer of resources from one line to another throughout the planning horizon should also be considered. A mathematical modelling framework is developed to solve the line planning problem with transfer of resources during a finite length planning horizon of multiple periods. We analyze whether or not multi-period solutions outperform single period solutions in terms of feasibility and relevant costs. The importance of demand variation on multi-period solutions is investigated. We evaluate the impact of resource transfer constraints on the effectiveness of solutions. We also study the effect of line type designs and question the choice of period lengths along with the problem parameters that are significant for and sensitive to the optimality of solutions.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-74662</identifier>
    <author>Guvenc Sahin</author>
    <submitter>Thomas Schlechte</submitter>
    <author>Amin Ahmadi</author>
    <author>Ralf Borndörfer</author>
    <author>Thomas Schlechte</author>
    <series>
      <title>ZIB-Report</title>
      <number>19-51</number>
    </series>
    <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="schlechte">Schlechte, Thomas</collection>
    <collection role="projects" number="MODAL-RailLab">MODAL-RailLab</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="projects" number="ECMath-MI7">ECMath-MI7</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/7466/ZR-19-51.pdf</file>
  </doc>
  <doc>
    <id>7397</id>
    <completedYear/>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2019-07-18</completedDate>
    <publishedDate>2019-07-18</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Re-optimizing ICE Rotations after a Tunnel Breakdown near Rastatt</title>
    <abstract language="eng">Planning    rolling    stock    movements    in    industrial    passenger    railway    applications    isa long-term process based on timetables which are also often valid for long periods of time. For these timetables and rotation plans, i.e., plans of railway vehicle movements are constructed as templates for these periods. During operation the rotation plans are affected by all kinds of unplanned events. An unusal example for that is the collapse of a tunnel ceiling near Rastatt in southern Germany due to construction works related to the renewal of the central station in Stuttgart. As a result the main railway connection between Stuttgart and Frankfurt am Main, located on top of the tunnel, had to be closed from August 12th to October 2nd 2017. This had a major impact on the railway network in southern Germany. Hence, all rotation plans and train schedules for both passenger and cargo traffic had to be revised. In this paper we focus on a case study for this situation and compute new rotation plans via mixed integer programming for  the  ICE  high  speed  fleet  of  DB  Fernverkehr  AG  one  of  the  largest  passenger  railway companies in Europe. In our approach we take care of some side constraints to ensure a smooth continuation of the rotation plans after the disruption has ended.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-73976</identifier>
    <enrichment key="SourceTitle">Appeared in: Proceedings of the 8th International Conference on Railway Operations Modelling and Analysis - RailNorrköping 2019</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <author>Boris Grimm</author>
    <submitter>Boris Grimm</submitter>
    <author>Ralf Borndörfer</author>
    <author>Thomas Schlechte</author>
    <series>
      <title>ZIB-Report</title>
      <number>19-02</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>case study</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>re-optimization</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>railway rolling stock optimization</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>mixed integer programming</value>
    </subject>
    <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="grimm">Grimm, Boris</collection>
    <collection role="persons" number="schlechte">Schlechte, Thomas</collection>
    <collection role="projects" number="MODAL-RailLab">MODAL-RailLab</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/7397/ZR-19-02.pdf</file>
  </doc>
  <doc>
    <id>7398</id>
    <completedYear/>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>160</pageFirst>
    <pageLast>168</pageLast>
    <pageNumber/>
    <edition/>
    <issue>069</issue>
    <volume>Linköping Electronic Conference Proceedings</volume>
    <type>conferenceobject</type>
    <publisherName>Linköping University Electronic Press, Linköpings universitet</publisherName>
    <publisherPlace>Linköping, Sweden</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2019-09-13</completedDate>
    <publishedDate>2019-06-17</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Re-optimizing ICE Rotations after a Tunnel Breakdown near Rastatt</title>
    <abstract language="eng">Planning    rolling    stock    movements    in    industrial    passenger    railway    applications    isa long-term process based on timetables which are also often valid for long periods of time. For these timetables and rotation plans, i.e., plans of railway vehicle movements are constructed as templates for these periods. During operation the rotation plans are affected by all kinds of unplanned events. An unusal example for that is the collapse of a tunnel ceiling near Rastatt in southern Germany due to construction works related to the renewal of the central station in Stuttgart. As a result the main railway connection between Stuttgart and Frankfurt am Main, located on top of the tunnel, had to be closed from August 12th to October 2nd 2017. This had a major impact on the railway network in southern Germany. Hence, all rotation plans and train schedules for both passenger and cargo traffic had to be revised. In this paper we focus on a case study for this situation and compute new rotation plans via mixed integer programming for  the  ICE  high  speed  fleet  of  DB  Fernverkehr  AG  one  of  the  largest  passenger  railway companies in Europe. In our approach we take care of some side constraints to ensure a smooth continuation of the rotation plans after the disruption has ended.</abstract>
    <parentTitle language="eng">Proceedings of the 8th International Conference on Railway Operations Modelling and Analysis - RailNorrköping 2019</parentTitle>
    <identifier type="issn">1650-3686</identifier>
    <identifier type="isbn">978-91-7929-992-7</identifier>
    <identifier type="url">http://www.ep.liu.se/ecp/article.asp?issue=069&amp;article=011&amp;volume=</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="SubmissionStatus">epub ahead of print</enrichment>
    <enrichment key="AcceptedDate">2019-03-22</enrichment>
    <enrichment key="PreprintUrn">urn:nbn:de:0297-zib-73976</enrichment>
    <enrichment key="FulltextUrl">http://www.ep.liu.se/ecp/069/011/ecp19069011.pdf</enrichment>
    <author>Ralf Borndörfer</author>
    <submitter>Boris Grimm</submitter>
    <author>Boris Grimm</author>
    <author>Thomas Schlechte</author>
    <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="grimm">Grimm, Boris</collection>
    <collection role="persons" number="schlechte">Schlechte, Thomas</collection>
    <collection role="projects" number="MODAL-RailLab">MODAL-RailLab</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>7399</id>
    <completedYear/>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>8</pageLast>
    <pageNumber/>
    <edition/>
    <issue>10</issue>
    <volume/>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2019-03-16</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Optimization of handouts for rolling stock rotations</title>
    <abstract language="eng">A railway operator creates (rolling stock) rotations in order to have a precise master plan for the operation of a timetable by railway vehicles. A rotation is considered as a cycle that multiply traverses a set of operational days while covering trips of the timetable. As it is well known, the proper creation of rolling stock rotations by, e.g., optimization algorithms is challenging and still a topical research subject. Nevertheless, we study a completely different but strongly related question in this paper, i.e.: How to visualize a rotation? For this purpose, we introduce a basic handout concept, which directly leads to the visualization, i.e., handout of a rotation. In our industrial application at DB Fernverkehr AG, the handout is exactly as important as the rotation itself. Moreover, it turns out that also other European railway operators use exactly the same methodology (but not terminology). Since a rotation can have many handouts of different quality, we show how to compute optimal ones through an integer program (IP) by standard software. In addition, a construction as well as an improvement heuristic are presented. Our computational results show that the heuristics are a very reliable standalone approach to quickly find near-optimal and even optimal handouts. The efficiency of the heuristics is shown via a computational comparison to the IP approach.</abstract>
    <parentTitle language="eng">Journal of Rail Transport Planning &amp; Management</parentTitle>
    <identifier type="doi">10.1016/j.jrtpm.2019.02.001</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="AcceptedDate">2019-02-20</enrichment>
    <enrichment key="PreprintUrn">urn:nbn:de:0297-zib-61430</enrichment>
    <author>Ralf Borndörfer</author>
    <submitter>Boris Grimm</submitter>
    <author>Boris Grimm</author>
    <author>Markus Reuther</author>
    <author>Thomas Schlechte</author>
    <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="grimm">Grimm, Boris</collection>
    <collection role="persons" number="schlechte">Schlechte, Thomas</collection>
    <collection role="projects" number="MODAL-RailLab">MODAL-RailLab</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>7396</id>
    <completedYear/>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>148</pageFirst>
    <pageLast>159</pageLast>
    <pageNumber>12</pageNumber>
    <edition/>
    <issue>069</issue>
    <volume>Linköping Electronic Conference Proceedings</volume>
    <type>conferenceobject</type>
    <publisherName>Linköping University Electronic Press, Linköpings universitet</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2019-09-13</completedDate>
    <publishedDate>2019-06-17</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Strategic Planning of Rolling Stock Rotations for Public Tenders</title>
    <abstract language="eng">Since railway companies have to apply for long-term public contracts to operate railway lines in public tenders, the question how they can estimate the operating cost for long-term periods adequately arises naturally. We consider a rolling stock rotation problem for a time period of ten years, which is based on a real world instance provided by an industry partner. We use a two stage approach for the cost estimation of the required rolling stock. In the first stage, we determine a weekly rotation plan. In the second stage, we roll out this weekly rotation plan for a longer time period and incorporate scheduled maintenance treatments. We present a heuristic approach and a mixed integer programming model to implement the process of the second stage. Finally, we discuss computational results for a real world tendering scenario.</abstract>
    <parentTitle language="eng">Proceedings of the 8th International Conference on Railway Operations Modelling and Analysis - RailNorrköping 2019</parentTitle>
    <identifier type="isbn">978-91-7929-992-7</identifier>
    <identifier type="issn">1650-3686</identifier>
    <identifier type="url">http://www.ep.liu.se/ecp/article.asp?issue=069&amp;article=009&amp;volume=</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="FulltextUrl">http://www.ep.liu.se/ecp/069/009/ecp19069009.pdf</enrichment>
    <author>Timo Berthold</author>
    <submitter>Stanley Schade</submitter>
    <author>Boris Grimm</author>
    <author>Markus Reuther</author>
    <author>Stanley Schade</author>
    <author>Thomas Schlechte</author>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="berthold">Berthold, Timo</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="projects" number="MODAL-SynLab">MODAL-SynLab</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>
  </doc>
  <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/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <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>1405</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2011-09-22</completedDate>
    <publishedDate>2011-09-22</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">A Hypergraph Model for Railway Vehicle Rotation Planning</title>
    <abstract language="eng">We propose a model for the integrated optimization of vehicle&#13;
  rotations and vehicle compositions in long distance railway passenger&#13;
  transport. The main contribution of the paper is a hypergraph model&#13;
  that is able to handle the challenging technical requirements as&#13;
  well as very general stipulations with respect to the ``regularity''&#13;
  of a schedule. The hypergraph model directly generalizes network&#13;
  flow models, replacing arcs with hyperarcs. Although NP-hard in&#13;
  general, the model is computationally well-behaved in practice.  High&#13;
  quality solutions can be produced in reasonable time using high&#13;
  performance Integer Programming techniques, in particular, column&#13;
  generation and rapid branching. We show that, in this way,&#13;
  large-scale real world instances of our cooperation partner DB&#13;
  Fernverkehr can be solved.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="serial">11-36</identifier>
    <identifier type="doi">/10.4230/OASIcs.ATMOS.2011.146</identifier>
    <identifier type="urn">urn:nbn:de:0030-drops-32746</identifier>
    <enrichment key="SourceTitle">Appeared in: 11th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems. Alberto Caprara and Spyros Kontogiannis (eds.) 2011, Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik, ISBN 978-3-939897-33-0, pp. 146-155, OpenAccess Series in Informatics (OASIcs), 20</enrichment>
    <author>Ralf Borndörfer</author>
    <submitter>Thomas Schlechte</submitter>
    <author>Markus Reuther</author>
    <author>Thomas Schlechte</author>
    <author>Steffen Weider</author>
    <series>
      <title>ZIB-Report</title>
      <number>11-36</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Rolling Stock Planning, Hypergraph Modeling, Integer Programming,    Column Generation, Rapid Branching</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="schlechte">Schlechte, Thomas</collection>
    <collection role="persons" number="weider">Weider, Steffen</collection>
    <collection role="projects" number="MATHEON-B22">MATHEON-B22</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/1405/ZR-11-36.pdf</file>
  </doc>
  <doc>
    <id>7550</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>2020-01-06</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">A Cut Separation Approach for the Rolling Stock Rotation Problem with Vehicle Maintenance</title>
    <abstract language="eng">For providing railway services the company’s railway rolling stock is one if not the most important ingredient. It decides about the number of passenger or cargo trips the company can offer, about the quality a passenger experiences the train ride&#13;
and it is often related to the image of the company itself. Thus, it is highly desired to&#13;
have the available rolling stock in the best shape possible. Moreover, in many countries, as Germany where our industrial partner DB Fernverkehr AG (DBF) is located, laws enforce regular vehicle inspections to ensure the safety of the passengers. This leads to rolling stock optimization problems with complex rules for vehicle maintenance. This problem is well studied in the literature for example see Maroti and Kroon 2005, or Cordeau et. al. 2001 for applications including vehicle maintenance. The contribution of this paper is a new algorithmic approach to solve the Rolling Stock Rotation Problem for the ICE high speed train fleet of DBF with included vehicle maintenance. It is based on a relaxation of a mixed integer&#13;
linear programming model with an iterative cut generation to enforce the feasibility of a solution of the relaxation in the solution space of the original problem. The resulting mixed integer linear programming model is based on a hypergraph approach presented in Borndörfer et. al. 2015. The new approach is tested on real world instances modeling different scenarios&#13;
for the ICE high speed train network in Germany and compared to the approaches&#13;
of Reuther 2017 that are in operation at DB Fernverkehr AG. The approach shows a significant reduction of the run time to produce solutions with comparable or even better objective function values.</abstract>
    <parentTitle language="deu">19th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2019)</parentTitle>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="doi">https://doi.org/10.4230/OASIcs.ATMOS.2019.1</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-75501</identifier>
    <author>Boris Grimm</author>
    <submitter>Boris Grimm</submitter>
    <author>Ralf Borndörfer</author>
    <author>Markus Reuther</author>
    <author>Thomas Schlechte</author>
    <series>
      <title>ZIB-Report</title>
      <number>19-61</number>
    </series>
    <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="grimm">Grimm, Boris</collection>
    <collection role="persons" number="schlechte">Schlechte, Thomas</collection>
    <collection role="projects" number="MODAL-RailLab">MODAL-RailLab</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/7550/ZR-19-61.pdf</file>
  </doc>
  <doc>
    <id>7543</id>
    <completedYear/>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1:1</pageFirst>
    <pageLast>1:12</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>75</volume>
    <type>conferenceobject</type>
    <publisherName>Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik</publisherName>
    <publisherPlace>Dagstuhl, Germany</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2019-09-14</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">A Cut Separation Approach for the Rolling Stock Rotation Problem with Vehicle Maintenance</title>
    <abstract language="eng">For providing railway services the company's railway rolling stock is one if not the most important ingredient. It decides about the number of passenger or cargo trips the company can offer, about the quality a passenger experiences the train ride and it is often related to the image of the company itself. Thus, it is highly desired to have the available rolling stock in the best shape possible. Moreover, in many countries, as Germany where our industrial partner DB Fernverkehr AG (DBF) is located, laws enforce regular vehicle inspections to ensure the safety of the passengers. This leads to rolling stock optimization problems with complex rules for vehicle maintenance. This problem is well studied in the literature for example see [Maróti and Kroon, 2005; Gábor Maróti and Leo G. Kroon, 2007], or [Cordeau et al., 2001] for applications including vehicle maintenance. The contribution of this paper is a new algorithmic approach to solve the Rolling Stock Rotation Problem for the ICE high speed train fleet of DBF with included vehicle maintenance. It is based on a relaxation of a mixed integer linear programming model with an iterative cut generation to enforce the feasibility of a solution of the relaxation in the solution space of the original problem. The resulting mixed integer linear programming model is based on a hypergraph approach presented in [Ralf Borndörfer et al., 2015]. The new approach is tested on real world instances modeling different scenarios for the ICE high speed train network in Germany and compared to the approaches of [Reuther, 2017] that are in operation at DB Fernverkehr AG. The approach shows a significant reduction of the run time to produce solutions with comparable or even better objective function values.</abstract>
    <parentTitle language="eng">19th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2019)</parentTitle>
    <identifier type="doi">10.4230/OASIcs.ATMOS.2019.1</identifier>
    <identifier type="url">https://drops.dagstuhl.de/opus/volltexte/2019/11413/</identifier>
    <enrichment key="Series">OpenAccess Series in Informatics (OASIcs)</enrichment>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="SubmissionStatus">epub ahead of print</enrichment>
    <enrichment key="FulltextUrl">https://drops.dagstuhl.de/opus/volltexte/2019/11413/pdf/OASIcs-ATMOS-2019-1.pdf</enrichment>
    <enrichment key="PreprintUrn">urn:nbn:de:0297-zib-75501</enrichment>
    <author>Boris Grimm</author>
    <submitter>Boris Grimm</submitter>
    <editor>Valentina Cacchiani</editor>
    <author>Ralf Borndörfer</author>
    <editor>Alberto Marchetti-Spaccamela</editor>
    <author>Markus Reuther</author>
    <author>Thomas Schlechte</author>
    <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="grimm">Grimm, Boris</collection>
    <collection role="persons" number="schlechte">Schlechte, Thomas</collection>
    <collection role="projects" number="MODAL-RailLab">MODAL-RailLab</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>5785</id>
    <completedYear/>
    <publishedYear>2016</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>465</pageFirst>
    <pageLast>472</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">The Cycle Embedding Problem</title>
    <abstract language="eng">Given two hypergraphs, representing a fine and a coarse "layer", and a cycle cover of the nodes of the coarse layer, the cycle embedding problem (CEP) asks for an embedding of the coarse cycles into the fine layer. The CEP is NP-hard for general hypergraphs, but it can be solved in polynomial time for graphs. We propose an integer rogramming formulation for the CEP that provides a complete escription of the CEP polytope for the graphical case. The CEP comes up in railway vehicle rotation scheduling. We present computational results for problem instances of DB Fernverkehr AG that justify a sequential coarse-first-fine-second planning approach.</abstract>
    <parentTitle language="eng">Operations Research Proceedings 2014</parentTitle>
    <identifier type="doi">10.1007/978-3-319-28697-6_65</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="PreprintUrn">urn:nbn:de:0297-zib-52788</enrichment>
    <author>Ralf Borndörfer</author>
    <submitter>Thomas Schlechte</submitter>
    <author>Marika Karbstein</author>
    <author>Julika Mehrgahrdt</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="schlechte">Schlechte, Thomas</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>7075</id>
    <completedYear/>
    <publishedYear>2018</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>687</pageFirst>
    <pageLast>692</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>Springer International Publishing</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Demand-Driven Line Planning with Selfish Routing</title>
    <abstract language="eng">Bus rapid transit systems in developing and newly industrialized countries are often operated at the limits of passenger capacity. In particular, demand during morning and afternoon peaks is hardly or even not covered with available line plans. In order to develop demand-driven line plans, we use two mathematical models in the form of integer programming problem formulations. While the actual demand data is specified with origin-destination pairs, the arc-based model considers the demand over the arcs derived from the origin-destination demand. In order to test the accuracy of the models in terms of demand satisfaction, we simulate the optimal solutions and compare number of transfers and travel times. We also question the effect of a selfish route choice behavior which in theory results in a Braess-like paradox by increasing the number of transfers when system capacity is increased with additional lines.</abstract>
    <parentTitle language="eng">Operations Research Proceedings 2017</parentTitle>
    <identifier type="doi">10.1007/978-3-319-89920-6_91</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="PreprintUrn">urn:nbn:de:0297-zib-64547</enrichment>
    <author>Malte Renken</author>
    <submitter>Niels Lindner</submitter>
    <author>Amin Ahmadi</author>
    <author>Ralf Borndörfer</author>
    <author>Guvenc Sahin</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="schlechte">Schlechte, Thomas</collection>
    <collection role="projects" number="MODAL-RailLab">MODAL-RailLab</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="projects" number="ECMath-MI7">ECMath-MI7</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>6751</id>
    <completedYear/>
    <publishedYear>2018</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>715</pageFirst>
    <pageLast>721</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>Springer International Publishing</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2018-05-26</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Structure-based Decomposition for Pattern-Detection for Railway Timetables</title>
    <abstract language="eng">We consider the problem of pattern detection in large scale &#13;
railway timetables. This problem arises in rolling stock optimization planning &#13;
in order to identify invariant sections of the timetable for&#13;
which a cyclic rotation plan is adequate. &#13;
We propose a dual reduction technique which leads to an decomposition &#13;
and enumeration method. Computational results for real &#13;
world instances demonstrate that the method is able to &#13;
produce optimal solutions as fast as standard MIP solvers.</abstract>
    <parentTitle language="eng">Operations Research Proceedings 2017</parentTitle>
    <identifier type="doi">10.1007/978-3-319-89920-6_95</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="PreprintUrn">urn:nbn:de:0297-zib-64525</enrichment>
    <enrichment key="AcceptedDate">2017-11-01</enrichment>
    <author>Stanley Schade</author>
    <submitter>Ambros Gleixner</submitter>
    <author>Thomas Schlechte</author>
    <author>Jakob Witzig</author>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="institutes" number="mip">Mathematical Optimization Methods</collection>
    <collection role="institutes" number="traffic">Mathematics of Transportation and Logistics</collection>
    <collection role="persons" number="schlechte">Schlechte, Thomas</collection>
    <collection role="projects" number="MIP-ZIBOPT">MIP-ZIBOPT</collection>
    <collection role="projects" number="MODAL-RailLab">MODAL-RailLab</collection>
    <collection role="projects" number="MODAL-SynLab">MODAL-SynLab</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>6764</id>
    <completedYear/>
    <publishedYear>2018</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>723</pageFirst>
    <pageLast>728</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>Springer International Publishing</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Timetable Sparsification by Rolling Stock Rotation Optimization</title>
    <abstract language="eng">Rolling stock optimization is a task that naturally arises by operating a railway system. It could be seen with different level of details. From a strategic perspective to have a rough plan which types of fleets to be bought to a more operational perspective to decide which coaches have to be maintained first. This paper presents a new approach to deal with rolling stock optimisation in case of a (long term) strike. Instead of constructing a completely new timetable for the strike period, we propose a mixed integer programming model that is able to choose appropriate trips from a given timetable to construct efficient tours of railway vehicles covering an optimized subset of trips, in terms of deadhead kilometers and importance of the trips. The decision which trip is preferred over the other is made by a simple evaluation method that is deduced from the network and trip defining data.</abstract>
    <parentTitle language="eng">Operations Research 2017</parentTitle>
    <identifier type="doi">10.1007/978-3-319-89920-6_96</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="PreprintUrn">urn:nbn:de:0297-zib-65948</enrichment>
    <enrichment key="AcceptedDate">2017-11-01</enrichment>
    <author>Ralf Borndörfer</author>
    <submitter>Stanley Schade</submitter>
    <author>Matthias Breuer</author>
    <author>Boris Grimm</author>
    <author>Markus Reuther</author>
    <author>Stanley Schade</author>
    <author>Thomas Schlechte</author>
    <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="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>
  </doc>
  <doc>
    <id>871</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2005-08-01</completedDate>
    <publishedDate>2005-08-01</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">A Column Generation Approach to Airline Crew Scheduling</title>
    <abstract language="eng">The airline crew scheduling problem deals with the construction of crew rotations in order to cover the flights of a given schedule at minimum cost. The problem involves complex rules for the legality and costs of individual pairings and base constraints for the availability of crews at home bases. A typical instance considers a planning horizon of one month and several thousand flights. We propose a column generation approach for solving airline crew scheduling problems that is based on a set partitioning model. We discuss algorithmic aspects such as the use of bundle techniques for the fast, approximate solution of linear programs, a pairing generator that combines Lagrangean shortest path and callback techniques, and a novel rapid branching'' IP heuristic. Computational results for a number of industrial instances are reported. Our approach has been implemented within the commercial crew scheduling system NetLine/Crew of Lufthansa Systems Berlin GmbH.</abstract>
    <identifier type="serial">05-37</identifier>
    <identifier type="opus3-id">871</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-8713</identifier>
    <enrichment key="SourceTitle">Appeared in: Operations Research Proceedings 2005. H.-D. Haasis et al. (eds.) Springer 2006, 343-348</enrichment>
    <author>Ralf Borndörfer</author>
    <author>Uwe Schelten</author>
    <author>Thomas Schlechte</author>
    <author>Steffen Weider</author>
    <series>
      <title>ZIB-Report</title>
      <number>05-37</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Integer Programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Airline Crew Scheduling</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Branch and Generate</value>
    </subject>
    <collection role="ddc" number="000">Informatik, Informationswissenschaft, allgemeine Werke</collection>
    <collection role="msc" number="90C10">Integer programming</collection>
    <collection role="institutes" number="">ZIB Allgemein</collection>
    <collection role="persons" number="borndoerfer">Borndörfer, Ralf</collection>
    <collection role="persons" number="schlechte">Schlechte, Thomas</collection>
    <collection role="persons" number="weider">Weider, Steffen</collection>
    <collection role="projects" number="LHS-CS">LHS-CS</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/871/ZR-05-37.pdf</file>
    <file>https://opus4.kobv.de/opus4-zib/files/871/ZR-05-37.ps</file>
  </doc>
  <doc>
    <id>1489</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>239</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>doctoralthesis</type>
    <publisherName>Südwestdeutscher Verlag für Hochschulschriften</publisherName>
    <publisherPlace>Saarbrücken, Germany</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2012-03-21</completedDate>
    <publishedDate>2012-03-21</publishedDate>
    <thesisDateAccepted>2012-02-15</thesisDateAccepted>
    <title language="eng">Railway Track Allocation: Models and Algorithms</title>
    <abstract language="eng">This thesis is about mathematical optimization for the efficient use of railway infrastructure. We address the &#13;
optimal allocation of the available railway track capacity - the track allocation problem.&#13;
This track allocation problem is a major challenge for a railway company, independent of &#13;
whether a free market, a private monopoly, or a public monopoly is given.&#13;
Planning and operating railway transportation systems is extremely hard due &#13;
to the combinatorial complexity of the underlying discrete optimization problems, &#13;
the technical intricacies, and the immense sizes of the problem instances. Mathematical models and optimization&#13;
techniques can result in huge gains for both railway customers and operators, e.g., &#13;
in terms of cost reductions or service quality improvements. &#13;
We tackle this challenge by developing novel mathematical models and associated innovative algorithmic &#13;
solution methods for large scale instances. This allows us to produce for the first time reliable &#13;
solutions for a real world instance, i.e., the Simplon corridor in Switzerland.&#13;
The opening chapter gives a comprehensive overview on railway planning problems.&#13;
This provides insights into the regulatory and technical framework, &#13;
it discusses the interaction of several planning steps, and identifies optimization potentials in &#13;
railway transportation. The remainder of the thesis is comprised of two major parts. &#13;
&#13;
&#13;
The first part is concerned with modeling railway systems to allow for resource and capacity analysis.&#13;
Railway capacity has basically two dimensions, a space dimension which are the physical &#13;
infrastructure elements as well as a time dimension that refers to the train movements, i.e., &#13;
occupation or blocking times, on the physical infrastructure. Railway safety systems operate &#13;
on the same principle all over the world. A train has to reserve infrastructure blocks for some time to pass through. &#13;
Two trains reserving the same block of the infrastructure within the same point in time is called block conflict.  &#13;
Therefore, models for railway capacity involve the definition &#13;
and calculation of reasonable running and associated reservation and &#13;
blocking times to allow for a conflict free allocation.&#13;
&#13;
In the second and main part of the thesis, the optimal track &#13;
allocation problem for macroscopic models of the railway system is considered.&#13;
The literature for related problems is surveyed. &#13;
A graph-theoretic model for the track allocation problem is &#13;
developed. In that model optimal track allocations correspond to &#13;
conflict-free paths in special time-expanded graphs.&#13;
Furthermore, we made considerable progress on solving track allocation problems by two &#13;
main features - a novel modeling approach for the macroscopic track &#13;
allocation problem and algorithmic improvements based on the&#13;
utilization of the bundle method.   &#13;
&#13;
Finally, we go back to practice and present in the last chapter several case &#13;
studies using the tools netcast and tsopt.&#13;
We provide a computational comparison of &#13;
our new models and standard packing models used in the literature. &#13;
Our computational experience indicates that our approach, i.e.,&#13;
``configuration models'', outperforms other models. Moreover, the rapid branching &#13;
heuristic and the bundle method enable us to produce high quality solutions for very large scale&#13;
instances, which has not been possible before. &#13;
In addition, we present results for a theoretical and rather visionary auction framework &#13;
for track allocation. We discuss several auction design questions and analyze experiments of &#13;
various auction simulations. &#13;
&#13;
The highlights are results for the Simplon corridor in Switzerland. &#13;
We optimized the train traffic through this tunnel using our models and &#13;
software tools.&#13;
To the best knowledge of the author and confirmed by several railway &#13;
practitioners this was the first time that fully automatically produced &#13;
track allocations on a macroscopic scale fulfill the requirements &#13;
of the originating microscopic model, withstand the evaluation in the &#13;
microscopic simulation tool OpenTrack, and exploit the infrastructure capacity.&#13;
This documents the success of our approach in practice and the usefulness &#13;
and applicability of mathematical optimization to railway track allocation.</abstract>
    <identifier type="isbn">978-3-8381-3222-8</identifier>
    <identifier type="url">http://opus.kobv.de/tuberlin/volltexte/2012/3427/pdf/schlechte_thomas.pdf</identifier>
    <identifier type="urn">urn:nbn:de:kobv:83-opus-34272</identifier>
    <advisor>Martin Grötschel</advisor>
    <author>Thomas Schlechte</author>
    <submitter>Thomas Schlechte</submitter>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>railway track allocation</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>large-scale integer programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>network aggregation</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>rapid branching</value>
    </subject>
    <collection role="ccs" number="G.">Mathematics of Computing</collection>
    <collection role="msc" number="90-XX">OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING</collection>
    <collection role="collections" number="">Dissertationen</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="schlechte">Schlechte, Thomas</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <thesisPublisher>Technische Universität Berlin</thesisPublisher>
    <thesisGrantor>Technische Universität Berlin</thesisGrantor>
    <file>https://opus4.kobv.de/opus4-zib/files/1489/thesisFinal.pdf</file>
  </doc>
  <doc>
    <id>3169</id>
    <completedYear>2006</completedYear>
    <publishedYear>2006</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>163</pageFirst>
    <pageLast>196</pageLast>
    <pageNumber/>
    <edition/>
    <issue>2</issue>
    <volume>1</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">An Auctioning Approach to Railway Slot Allocation</title>
    <parentTitle language="eng">Competition and Regulation in Network Industries</parentTitle>
    <enrichment key="PreprintUrn">urn:nbn:de:0297-zib-8786</enrichment>
    <author>Ralf Borndörfer</author>
    <author>Martin Grötschel</author>
    <author>Sascha Lukac</author>
    <author>Kay Mitusch</author>
    <author>Thomas Schlechte</author>
    <author>Sören Schultz</author>
    <author>Andreas Tanner</author>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="borndoerfer">Borndörfer, Ralf</collection>
    <collection role="persons" number="groetschel">Grötschel, Martin</collection>
    <collection role="persons" number="schlechte">Schlechte, Thomas</collection>
    <collection role="projects" number="Trassenbörse">Trassenbörse</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
  <doc>
    <id>10199</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>2025-11-07</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Scheduling for German Road Inspectors</title>
    <abstract language="eng">For the yearly over 500,000 vehicle inspections of the German Federal Logistics and Mobility Office (BALM), crew rosters must be scheduled to efficiently achieve Germany's road inspection control targets. For that, we present a model to solve the respective duty scheduling and crew rostering problem in order to obtain duty rosters that comply with numerous legal regulations while maximizing the 'control success' to achieve the control targets. We formulate the Template Assignment Problem, which can be modelled as a large scale mixed-integer linear program. Here, feasible combinations of control topics are assigned to the duties using a hypergraph approach. The model is used in production by BALM, and we prove its effectiveness on a number of real-world instances.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-101999</identifier>
    <enrichment key="opus.source">publish</enrichment>
    <author>Patricia Ebert</author>
    <submitter>Patricia Ebert</submitter>
    <author>Thomas Schlechte</author>
    <author>Stephan Schwartz</author>
    <series>
      <title>ZIB-Report</title>
      <number>25-13</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>scheduling</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>rostering</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>mixed-integer linear program</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>crew scheduling</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>hypergraph</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="schlechte">Schlechte, Thomas</collection>
    <collection role="persons" number="schwartz">Schwartz, Stephan</collection>
    <collection role="projects" number="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="institutes" number="neo">Network Optimization</collection>
    <collection role="projects" number="MODAL-MobilityLab">MODAL-MobilityLab</collection>
    <collection role="persons" number="ebert">Ebert, Patricia</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/10199/Scheduling_for_German_Road_Inspectors.pdf</file>
  </doc>
  <doc>
    <id>1642</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2012-11-06</completedDate>
    <publishedDate>2012-11-06</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Integrated Optimization of Rolling Stock Rotations for Intercity Railways</title>
    <abstract language="eng">This paper provides a highly integrated solution approach for rolling stock &#13;
planning problems in the context of intercity passenger traffic. The main &#13;
contributions are a generic hypergraph based mixed integer programming &#13;
model and an integrated algorithm for the considered rolling stock rotation &#13;
planning problem. The new developed approach is able to handle a very large&#13;
set of industrial railway requirements, such as vehicle composition, &#13;
maintenance constraints, infrastructure capacity, and regularity aspects. &#13;
By the integration of this large bundle of technical railway aspects, we show &#13;
that our approach has the power to produce implementable rolling stock &#13;
rotations for our industrial cooperation partner DB Fernverkehr. &#13;
This is the first time that the rolling stock rotations at DB Fernverkehr &#13;
could be optimized by an automated system utilizing advanced mathematical &#13;
programming techniques.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-16424</identifier>
    <author>Markus Reuther</author>
    <submitter>Markus Reuther</submitter>
    <author>Ralf Borndörfer</author>
    <author>Thomas Schlechte</author>
    <author>Steffen Weider</author>
    <series>
      <title>ZIB-Report</title>
      <number>12-39</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Mixed Integer Programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Railway Optimization</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Rolling Stock Rostering</value>
    </subject>
    <collection role="ccs" number="G.">Mathematics of Computing</collection>
    <collection role="pacs" number="00.00.00">GENERAL</collection>
    <collection role="msc" number="90-XX">OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="schlechte">Schlechte, Thomas</collection>
    <collection role="persons" number="weider">Weider, Steffen</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/1642/vrp.pdf</file>
  </doc>
  <doc>
    <id>1899</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2013-07-19</completedDate>
    <publishedDate>2013-07-19</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">The Freight Train Routing Problem</title>
    <abstract language="eng">We consider the following freight train routing problem (FTRP). Given is a&#13;
transportation network with fixed routes for passenger trains and a&#13;
set of freight trains (requests), each defined by an origin and&#13;
destination station pair. The objective is to calculate a feasible&#13;
route for each freight train such that a sum of all expected delays and&#13;
all running times is minimal. Previous research concentrated on&#13;
microscopic train routings for junctions or inside major stations. Only&#13;
recently approaches were developed to tackle larger corridors or even&#13;
networks. We investigate the routing problem from a strategic&#13;
perspective, calculating the routes in a macroscopic transportation&#13;
network of Deutsche Bahn AG. Here macroscopic refers to an aggregation of &#13;
complex real-world structures are into fewer network elements. Moreover, the &#13;
departure and arrival times of freight trains are approximated. &#13;
The problem has a strategic&#13;
character since it asks only for a coarse routing through the network&#13;
without the precise timings. We give a mixed-integer nonlinear programming~(MINLP) &#13;
formulation for FTRP, which is a multi-commodity flow model on a time-expanded &#13;
graph with additional routing constraints. The model's nonlinearities are due to &#13;
an algebraic approximation of the delays of the trains on the arcs of&#13;
the network &#13;
by capacity restraint functions. The MINLP is reduced to a mixed-integer linear model~(MILP) &#13;
by piecewise linear approximation. The latter is solved by a state of the art MILP solver for various real-world test instances.</abstract>
    <identifier type="urn">urn:nbn:de:0297-zib-18991</identifier>
    <author>Ralf Borndörfer</author>
    <submitter>Torsten Klug</submitter>
    <author>Armin Fügenschuh</author>
    <author>Torsten Klug</author>
    <author>Thilo Schang</author>
    <author>Thomas Schlechte</author>
    <author>Hanno Schülldorf</author>
    <series>
      <title>ZIB-Report</title>
      <number>13-36</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Mixed-Integer Nonlinear Programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>multi-commodity flows</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>freight train routing</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="fuegenschuh">Fügenschuh, Armin</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="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/1899/ZR-13-36.pdf</file>
  </doc>
  <doc>
    <id>8254</id>
    <completedYear/>
    <publishedYear>2021</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>2021-06-09</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Microscopic Timetable Optimization for a Moving Block System</title>
    <abstract language="eng">We present an optimization model which is capable of routing and ordering trains on a microscopic level under a moving block regime. Based on a general timetabling definition (GTTP) that allows the plug in of arbitrarily detailed methods to compute running and headway times, we describe a layered graph approach using velocity expansion, and develop a mixed integer linear programming formulation. Finally, we present promising results for a German corridor scenario with mixed traffic, indicating that applying branch-and-cut to our model is able to solve reasonably sized instances with up to hundred trains to optimality.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-82547</identifier>
    <enrichment key="opus.source">publish</enrichment>
    <author>Ralf Borndörfer</author>
    <submitter>Niels Lindner</submitter>
    <author>Jonas Denißen</author>
    <author>Simon Heller</author>
    <author>Torsten Klug</author>
    <author>Michael Küpper</author>
    <author>Niels Lindner</author>
    <author>Markus Reuther</author>
    <author>Thomas Schlechte</author>
    <author>Andreas Söhlke</author>
    <author>William Steadman</author>
    <series>
      <title>ZIB-Report</title>
      <number>21-13</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Moving Block</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Railway Track Allocation</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Railway Timetabling</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Train Routing</value>
    </subject>
    <collection role="ccs" number="J.">Computer Applications</collection>
    <collection role="msc" number="90-XX">OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING</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="MODAL-Gesamt">MODAL-Gesamt</collection>
    <collection role="persons" number="reuther">Reuther, Markus</collection>
    <collection role="persons" number="lindner">Lindner, Niels</collection>
    <collection role="institutes" number="neo">Network Optimization</collection>
    <collection role="projects" number="MODAL-MobilityLab">MODAL-MobilityLab</collection>
    <thesisPublisher>Zuse Institute Berlin (ZIB)</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-zib/files/8254/ZR-21-13.pdf</file>
  </doc>
  <doc>
    <id>1408</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2011-09-29</completedDate>
    <publishedDate>2011-09-29</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Solving steel mill slab design problems</title>
    <abstract language="eng">The steel mill slab design problem from the CSPLIB is a combinatorial&#13;
optimization problem motivated by an application of the steel industry. It&#13;
has been widely studied in the constraint programming community.  Several&#13;
methods were proposed to solve this problem. A steel mill slab library was&#13;
created which contains 380 instances. A closely related binpacking problem&#13;
called the multiple knapsack problem with color constraints, originated&#13;
from the same industrial problem, was discussed in the integer programming&#13;
community. In particular, a simple integer program for this problem has&#13;
been given by Forrest et al. The aim of this paper is to bring these&#13;
different studies together. Moreover, we adapt the model of Forrest et&#13;
al. for the steel mill slab design problem. Using this model and a&#13;
state-of-the-art integer program solver all instances of the steel mill&#13;
slab library can be solved efficiently to optimality.  We improved,&#13;
thereby, the solution values of 76 instances compared to previous results.&#13;
Finally, we consider a recently introduced variant of the steel mill slab&#13;
design problem, where within all solutions which minimize the leftover one&#13;
is interested in a solution which requires a minimum number of slabs. For&#13;
that variant we introduce two approaches and solve all instances of the&#13;
steel mill slab library with this slightly changed objective function to&#13;
optimality.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="serial">11-38</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-14089</identifier>
    <identifier type="doi">10.1007/s10601-011-9113-8</identifier>
    <enrichment key="SourceTitle">Appeared in: Constraints 17 (2012) 39-50</enrichment>
    <author>Stefan Heinz</author>
    <submitter>Stefan Heinz</submitter>
    <author>Thomas Schlechte</author>
    <author>Rüdiger Stephan</author>
    <author>Michael Winkler</author>
    <series>
      <title>ZIB-Report</title>
      <number>11-38</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>steel mill slab design problem</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>multiple knapsack problem with color constraints</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>integer programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>set partitioning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>binpacking with side constraints</value>
    </subject>
    <collection role="msc" number="90-XX">OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING</collection>
    <collection role="msc" number="90Cxx">Mathematical programming [See also 49Mxx, 65Kxx]</collection>
    <collection role="msc" number="90C90">Applications of mathematical programming</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="heinz">Heinz, Stefan</collection>
    <collection role="persons" number="schlechte">Schlechte, Thomas</collection>
    <collection role="persons" number="michael.winkler">Winkler, Michael</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/1408/ZR-11-38.pdf</file>
  </doc>
  <doc>
    <id>1794</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2013-03-04</completedDate>
    <publishedDate>2013-03-04</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">A Direct Comparison of Physical Block Occupancy Versus Timed Block Occupancy in Train Timetabling Formulations</title>
    <abstract language="eng">Two fundamental mathematical formulations for railway timetabling are compared on a common set of sample problems, representing both multiple track high density services in Europe and single track bidirectional operations in North America. One formulation, ACP, enforces against conflicts by constraining time intervals between trains, while the other formulation, HGF, monitors physical occupation of controlled track segments. The results demonstrate that both ACP and HGF return comparable solutions in the aggregate, with some significant differences in select instances, and a pattern of significant differences in performance and constraint enforcement overall.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-17946</identifier>
    <identifier type="doi">10.1016/j.tre.2013.04.003</identifier>
    <enrichment key="SourceTitle">To appear in: Transportation Research Part E: Logistics and Transportation Review.</enrichment>
    <author>Steven Harrod</author>
    <submitter>Thomas Schlechte</submitter>
    <author>Thomas Schlechte</author>
    <series>
      <title>ZIB-Report</title>
      <number>13-18</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Railway Scheduling</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Train Timetabling</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Track Allocation</value>
    </subject>
    <collection role="ccs" number="G.">Mathematics of Computing</collection>
    <collection role="msc" number="90-XX">OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING</collection>
    <collection role="institutes" number="optimization">Mathematical Optimization</collection>
    <collection role="persons" number="schlechte">Schlechte, Thomas</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/1794/ZR-13-18.pdf</file>
  </doc>
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