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  <doc>
    <id>8821</id>
    <completedYear/>
    <publishedYear>2022</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>11:1</pageFirst>
    <pageLast>11:8</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>106</volume>
    <type>conferenceobject</type>
    <publisherName>Schloss Dagstuhl -- Leibniz-Zentrum für Informatik</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>2022-09-06</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Does Laziness Pay Off? - A Lazy-Constraint Approach to Timetabling</title>
    <abstract language="eng">Timetabling is a classical and complex task for public transport operators as well as for railway undertakings. The general question is: Which vehicle is taking which route through the transportation network in which order? In this paper, we consider the special setting to find optimal timetables for railway systems under a moving block regime. We directly set up on our work of [8 ], i.e., we consider the same model formulation and real-world instances of a moving block headway system. In this paper, we present a repair heuristic and a lazy-constraint approach utilizing the callback features of Gurobi, see [3]. We provide an experimental study of the different algorithmic approaches for a railway network with 100 and up to 300 train requests. The computational results show that the lazy-constraint approach together with the repair heuristic significantly improves our previous approaches.</abstract>
    <parentTitle language="eng">22nd Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2022)</parentTitle>
    <identifier type="doi">10.4230/OASIcs.ATMOS.2022.11</identifier>
    <enrichment key="Series">Open Access Series in Informatics (OASIcs)</enrichment>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <author>Torsten Klug</author>
    <submitter>Thomas Schlechte</submitter>
    <author>Markus Reuther</author>
    <author>Thomas Schlechte</author>
    <collection role="institutes" number="optimization">Mathematical Optimization</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="institutes" number="neo">Network Optimization</collection>
    <collection role="projects" number="MODAL-MobilityLab">MODAL-MobilityLab</collection>
    <collection role="institutes" number="aopt">Applied Optimization</collection>
  </doc>
</export-example>
