Failure Based Variable Ordering Heuristics for Solving CSPs (Short Paper)

Authors Hongbo Li , Minghao Yin, Zhanshan Li

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Hongbo Li
  • School of Information Science and Technology, Northeast Normal University, Changchun, China
Minghao Yin
  • School of Information Science and Technology, Northeast Normal University, Changchun, China
Zhanshan Li
  • College of Computer Science and Technology, Jilin University, Changchun, China

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Hongbo Li, Minghao Yin, and Zhanshan Li. Failure Based Variable Ordering Heuristics for Solving CSPs (Short Paper). In 27th International Conference on Principles and Practice of Constraint Programming (CP 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 210, pp. 9:1-9:10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)


Variable ordering heuristics play a central role in solving constraint satisfaction problems. In this paper, we propose failure based variable ordering heuristics. Following the fail first principle, the new heuristics use two aspects of failure information collected during search. The failure rate heuristics consider the failure proportion after the propagations of assignments of variables and the failure length heuristics consider the length of failures, which is the number of fixed variables composing a failure. We performed a vast experiments in 41 problems with 1876 MiniZinc instances. The results show that the failure based heuristics outperform the existing ones including activity-based search, conflict history search, the refined weighted degree and correlation-based search. They can be new candidates of general purpose variable ordering heuristics for black-box CSP solvers.

Subject Classification

ACM Subject Classification
  • Computing methodologies
  • Constraint Satisfaction Problem
  • Variable Ordering Heuristic
  • Failure Rate
  • Failure Length


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