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  <subfield code="a">FloeMTITS2011</subfield> 
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<subfield code="p">TRANSP-OR</subfield>
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<subfield code="a">TALK</subfield>
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  <subfield code="a">Flötteröd, Gunnar</subfield> 
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  <subfield code="a">Bierlaire, Michel</subfield> 
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<subfield code="a">
Metropolis-Hastings sampling of paths</subfield>
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<subfield code="c">2011</subfield>
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<subfield code="a">
Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS)</subfield>
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KU Leuven, Leuven, Belgium</subfield>
<subfield code="d">June 22, 2011</subfield>
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<subfield code="a">
We consider the previously unsolved problem of sampling paths according to a given distribution from a general network. The problem is difficult because of the combinatorial number of alternatives, which prohibits a complete enumeration of all paths and hence also forbids to compute the normalizing constant of the sampling distribution. The problem is important because the ability to sample from a known distribution introduces mathematical rigor into many applications, including the estimation of choice models with sampling of alternatives that can be formalized as paths in a decision network (most obviously route choice), probabilistic map matching, dynamic traffic assignment, and route guidance. (C) 2012 Elsevier Ltd. All rights reserved.</subfield>
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