Extracting Minimum Unsatisfiable Cores with a Greedy Genetic Algorithm

  • Jianmin Zhang
  • Sikun Li
  • Shengyu Shen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4304)


Explaining the causes of infeasibility of Boolean formulas has practical applications in various fields. We are generally interested in a minimum explanation of infeasibility that excludes irrelevant information. A smallest-cardinality unsatisfiable subset, called a minimum unsatisfiable core, can provide a succinct explanation of infeasibility and is valuable for applications. However little attention has been concentrated on extraction of minimum unsatisfiable cores. In this paper, we propose an efficient greedy genetic algorithm to derive an exact or nearly exact minimum unsatisfiable core. It takes advantage of the relationship between maximal satisfiability and minimum unsatisfiability. We report experimental results on practical benchmarks, as compared with the branch-and-bound algorithm and the ant colony optimization.


Problem Instance Greedy Algorithm Conjunctive Normal Form Boolean Formula Conjunctive Normal Form Formula 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jianmin Zhang
    • 1
  • Sikun Li
    • 1
  • Shengyu Shen
    • 1
  1. 1.School of Computer ScienceNational University of Defense TechnologyChangShaChina

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