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Learning Good Variable Orderings

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2833))

Abstract

Variable ordering heuristics try to reduce the cost of searching for a solution to a constraint satisfaction problem (CSP). On real problems that have non-binary and non-uniform constraints it is harder to make a good choice of variable ordering: surprisingly little is known about when and why variable ordering heuristics perform well. In an attempt to address this problem we present initial problem-specific investigations into variable orderings.

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References

  1. Petrie, K.E., Smith, B.M.: Symmetry Breaking in Graceful Graphs. In: Rossi, F. (ed.) CP 2003. LNCS, vol. 2833, pp. 930–934. Springer, Heidelberg (2003)

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  2. Sturdy, P.: Learning Good Variable Orderings. Technical Report APES-64-2003, APES Research Group (July 2003), Available from http://www.dcs.st-and.ac.uk/~apes/apesreports.html

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© 2003 Springer-Verlag Berlin Heidelberg

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Sturdy, P. (2003). Learning Good Variable Orderings. In: Rossi, F. (eds) Principles and Practice of Constraint Programming – CP 2003. CP 2003. Lecture Notes in Computer Science, vol 2833. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45193-8_121

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  • DOI: https://doi.org/10.1007/978-3-540-45193-8_121

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-20202-8

  • Online ISBN: 978-3-540-45193-8

  • eBook Packages: Springer Book Archive

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