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        <identifier>oai:drops-oai.dagstuhl.de:2148</identifier>
        <datestamp>2024-03-06T10:28:39Z</datestamp>
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          <dc:title>Accelerating Time-Dependent Multi-Criteria Timetable Information is Harder Than Expected</dc:title>
          <dc:creator>Berger, Annabell</dc:creator>
          <dc:creator>Delling, Daniel</dc:creator>
          <dc:creator>Gebhardt, Andreas</dc:creator>
          <dc:creator>Müller-Hannemann, Matthias</dc:creator>
          <dc:subject>Timetable information</dc:subject>
          <dc:subject>multi-criteria search</dc:subject>
          <dc:subject>time-dependent networks</dc:subject>
          <dc:subject>arc flags</dc:subject>
          <dc:subject>contraction Timetable information</dc:subject>
          <dc:subject>multi-criteria search</dc:subject>
          <dc:subject>time-dependent networks</dc:subject>
          <dc:subject>arc flags</dc:subject>
          <dc:subject>contraction</dc:subject>
          <dc:description>Speeding up multi-criteria search in real timetable information systems&#13;
remains a challenge in spite of impressive progress achieved in recent years&#13;
for related problems in road networks.&#13;
Our goal is to perform multi-criteria range queries, that is, to find all &#13;
Pareto-optimal connections with respect to travel time and number of transfers &#13;
within a given start time interval. This problem can be modeled as a path &#13;
search problem in a time- and event-dependent graph. In this paper, we investigate two key speed-up techniques for a multi-criteria variant of \textsc{Dijkstra}'s algorithm --- arc flags and contraction --- which seem to be strong candidates for railway networks, too. &#13;
We describe in detail how these two techniques have to be adapted for a multi-criteria scenario and explain why we can expect only marginal speed-ups (compared to observations in road networks) from a direct implementation. Based on these insights we extend traditional arc-flags to \emph{time-period flags} and introduce \emph{route contraction} as a substitute for node contraction.&#13;
A computational study on real queries demonstrates that these techniques &#13;
combined with goal-directed search lead to a speed-up of factor 13.08 over the baseline variant for range queries for a full day.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Annabell Berger and Daniel Delling and Andreas Gebhardt and Matthias Müller-Hannemann</dc:contributor>
          <dc:date>2009</dc:date>
          <dc:relation>Is Part Of OASIcs, Volume 12, 9th Workshop on Algorithmic Approaches for Transportation Modeling, Optimization, and Systems (ATMOS'09) (2009)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
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          <dc:identifier>doi:10.4230/OASIcs.ATMOS.2009.2148</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-21481</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ATMOS.2009.2148</dc:identifier>
          <dc:language>eng</dc:language>
          <dc:rights>https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode</dc:rights>
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