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Improving degree-based variable ordering heuristics for solving constraint satisfaction problems

Author

Listed:
  • Hongbo Li

    (Jilin University
    Northeast Normal University)

  • Yanchun Liang

    (Jilin University)

  • Ning Zhang

    (University of Missouri)

  • Jinsong Guo

    (University of Oxford)

  • Dong Xu

    (University of Missouri)

  • Zhanshan Li

    (Jilin University)

Abstract

In this paper, we improved two classical degree-based variable ordering heuristics, $$\frac{\textit{Dom}}{\textit{Ddeg}}$$ Dom Ddeg and $$\frac{\textit{Dom}}{\textit{Wdeg}}$$ Dom Wdeg . We propose a method using the summation of constraint tightness in degree-based heuristics. We also propose two methods to calculate dynamic constraint tightness for binary extensional constraints and non-binary intensional constraints respectively. Our work shows how constraint tightness can be practically used to guide search. We performed a number of experiments on some benchmark instances. The results have shown that, the new heuristics improve the classical ones by both computational time and search tree nodes and they are more efficient than some other successful heuristics on the instances where the classical heuristics work well.

Suggested Citation

  • Hongbo Li & Yanchun Liang & Ning Zhang & Jinsong Guo & Dong Xu & Zhanshan Li, 2016. "Improving degree-based variable ordering heuristics for solving constraint satisfaction problems," Journal of Heuristics, Springer, vol. 22(2), pages 125-145, April.
  • Handle: RePEc:spr:joheur:v:22:y:2016:i:2:d:10.1007_s10732-015-9305-2
    DOI: 10.1007/s10732-015-9305-2
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    Cited by:

    1. Hongbo Li & Guozhong Feng & Minghao Yin, 2020. "On combining variable ordering heuristics for constraint satisfaction problems," Journal of Heuristics, Springer, vol. 26(4), pages 453-474, August.

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