Abstract
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.
This work is supported by the National Science Foundation of China (NSFC) under grant No. 60603088.
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Zhang, J., Li, S., Shen, S. (2006). Extracting Minimum Unsatisfiable Cores with a Greedy Genetic Algorithm. In: Sattar, A., Kang, Bh. (eds) AI 2006: Advances in Artificial Intelligence. AI 2006. Lecture Notes in Computer Science(), vol 4304. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11941439_89
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DOI: https://doi.org/10.1007/11941439_89
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