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          <dc:title>15. Maintenance of Multi-level Overlay Graphs for Timetable Queries</dc:title>
          <dc:creator>Bruera, Francesco</dc:creator>
          <dc:creator>Cicerone, Serafino</dc:creator>
          <dc:creator>D'Angelo, Gianlorenzo</dc:creator>
          <dc:creator>Di Stefano, Gabriele</dc:creator>
          <dc:creator>Frigioni, Daniele</dc:creator>
          <dc:subject>Timetable Queries</dc:subject>
          <dc:subject>Speed-up techniques for shortest paths</dc:subject>
          <dc:subject>Dynamic maintenance of shortest paths</dc:subject>
          <dc:description>In railways systems the timetable is typically represented as a&#13;
weighted digraph on which itinerary queries are answered by&#13;
shortest path algorithms, usually running Dijkstra's algorithm.&#13;
Due to the continuously growing size of real-world graphs, there&#13;
is a constant need for faster algorithms and many techniques have&#13;
been devised to heuristically speed up Dijkstra's algorithm. One&#13;
of these techniques is the multi-level overlay graph, that&#13;
has been recently introduced and shown to be experimentally&#13;
efficient, especially when applied to timetable information.&#13;
&#13;
In many practical application major disruptions to the normal&#13;
operation cannot be completely avoided because of the complexity&#13;
of the underlying systems. Timetable information&#13;
update after disruptions is considered one of the weakest points&#13;
in current railway systems, and this determines the need for an&#13;
effective online redesign and update of the shortest paths&#13;
information as a consequence of disruptions.&#13;
&#13;
In this paper, we make a step forward toward this direction by&#13;
showing some theoretical properties of multi-level overlay graphs&#13;
that lead us to the definition of a new data structure for the&#13;
dynamic maintenance of a multi-level overlay graph of a given&#13;
graph G while weight decrease or weight increase operations are&#13;
performed on G. Our solution is theoretically faster than the&#13;
recomputation from scratch and allows fast queries.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Francesco Bruera and Serafino Cicerone and Gianlorenzo D'Angelo and Gabriele Di Stefano and Daniele Frigioni</dc:contributor>
          <dc:date>2007</dc:date>
          <dc:relation>Is Part Of OASIcs, Volume 7, 7th Workshop on Algorithmic Approaches for Transportation Modeling, Optimization, and Systems (ATMOS'07) (2007)</dc:relation>
          <dc:type>InProceedings</dc:type>
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          <dc:identifier>doi:10.4230/OASIcs.ATMOS.2007.1171</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-11717</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ATMOS.2007.1171</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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