Journal of Heuristics

, Volume 22, Issue 2, pp 125–145 | Cite as

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

  • Hongbo Li
  • Yanchun Liang
  • Ning Zhang
  • Jinsong Guo
  • Dong Xu
  • Zhanshan Li
Article
  • 304 Downloads

Abstract

In this paper, we improved two classical degree-based variable ordering heuristics, \(\frac{\textit{Dom}}{\textit{Ddeg}}\) and \(\frac{\textit{Dom}}{\textit{Wdeg}}\). 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.

Keywords

Constraint satisfaction problem Variable ordering heuristic Weighted degree Constraint tightness 

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Hongbo Li
    • 1
    • 2
  • Yanchun Liang
    • 1
  • Ning Zhang
    • 4
  • Jinsong Guo
    • 3
  • Dong Xu
    • 4
  • Zhanshan Li
    • 1
  1. 1.Key Laboratory for Symbol Computation and Knowledge Engineering of National Education Ministry, College of Computer Science and TechnologyJilin UniversityChangchunChina
  2. 2.School of Computer Science and Information TechnologyNortheast Normal UniversityChangchunChina
  3. 3.Department of Computer ScienceUniversity of OxfordOxfordUK
  4. 4.Department of Computer Science and Christopher S. Bond Life Sciences CenterUniversity of MissouriColumbiaUSA

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