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          <dc:title>11. Multistage Methods for Freight Train Classification</dc:title>
          <dc:creator>Jacob, Riko</dc:creator>
          <dc:creator>Marton, Peter</dc:creator>
          <dc:creator>Maue, Jens</dc:creator>
          <dc:creator>Nunkesser, Marc</dc:creator>
          <dc:subject>Freight trains</dc:subject>
          <dc:subject>sorting algorithms</dc:subject>
          <dc:subject>train classification</dc:subject>
          <dc:subject>shunting</dc:subject>
          <dc:subject>cargo</dc:subject>
          <dc:description>In this paper we establish a consistent encoding of freight train classification methods.&#13;
This encoding scheme presents a powerful tool for efficient presentation and analysis of classification methods, which we successfully apply to illustrate the most relevant historic results from a more theoretical point of view.&#13;
We analyze their performance precisely and develop new classification methods making use of the inherent optimality condition of the encoding.&#13;
We conclude with deriving optimal algorithms and complexity results for restricted real-world settings.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Riko Jacob and Peter Marton and Jens Maue and Marc Nunkesser</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>
          <dc:type>Text</dc:type>
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          <dc:identifier>doi:10.4230/OASIcs.ATMOS.2007.1179</dc:identifier>
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          <dc:language>eng</dc:language>
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