Breaking Row and Column Symmetries in Matrix Models
CP '02 Proceedings of the 8th International Conference on Principles and Practice of Constraint Programming
Efficient haplotype inference with boolean satisfiability
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Breaking instance-independent symmetries in exact graph coloring
Journal of Artificial Intelligence Research
SAT in bioinformatics: making the case with haplotype inference
SAT'06 Proceedings of the 9th international conference on Theory and Applications of Satisfiability Testing
Solving difficult instances of Boolean satisfiability in the presence of symmetry
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Boosting Haplotype Inference with Local Search
Constraints
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Symmetry occurs naturally in many computational problems. The use of symmetry breaking techniques for solving search problems reduces the search space and therefore is expected to reduce the search time. Recent advances in breaking symmetries in SAT models are mainly focused on the identification of permutable variables via graph automorphism. These symmetries are denoted as instance-dependent, and although shown to be effective for different problem instances, the advantages of their generalised use in SAT are far from clear. Indeed, in many cases symmetry breaking predicates can introduce significant computational overhead, rendering ineffective the use of symmetry breaking. In contrast, in other domains, symmetry breaking is usually achieved by identifying instance-independent symmetries, often with promising experimental results. This paper studies the use of instance-independent symmetry breaking predicates in SAT. A concrete application is considered, and techniques for symmetry breaking in matrix models from CP are used. Our results indicate that instance-independent symmetry breaking predicates for matrix models can be significantly more effective than instance-dependent symmetry breaking predicates.