Adaptive Enumeration Strategies and Metabacktracks for Constraint Solving

  • Eric Monfroy
  • Carlos Castro
  • Broderick Crawford
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4243)


In Constraint Programming, enumeration strategies are crucial for resolution performances. The effect of strategies is generally unpredictable. In a previous work, we proposed to dynamically change strategies showing bad performances, and to use metabacktrack to restore better states when bad decisions were made. In this paper, we design and evaluate strategies to improve resolution performances of a set of problems. Experimental results show the effectiveness of our approach.


Search Tree Constraint Program Constraint Satisfaction Problem Static Strategy Enumeration Strategy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Eric Monfroy
    • 1
    • 2
  • Carlos Castro
    • 1
  • Broderick Crawford
    • 1
    • 3
  1. 1.Universidad Técnica Federico Santa MaríaValparaísoChile
  2. 2.LINAUniversité de NantesFrance
  3. 3.Pontificia Universidad Católica de ValparaísoChile

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