Just-in-Time Hierarchical Constraint Decomposition

Authors

  • Valentin Mayer-Eichberger University of New South Wales and NICTA

DOI:

https://doi.org/10.1609/aaai.v29i1.9733

Keywords:

SAT and CSP: Modeling/Formulations

Abstract

Lazy Clause Generation (LCG) solvers dominate the current constraint programming competitions. These solvers successfully combine systematic propagation based search, global constraints and conflict clause learning from SAT solving into a hybrid approach. My research project extends the LCG methodology by using a mix of eager and lazy encodings and a richer set of constraint decompositions. Global Constraints exhibit a whole hierarchy of different decomposition into more basic constraints. In our work we want to take advantage of such hierarchies and identify criteria on how constraints could be decomposed before and during search.

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Published

2015-03-04

How to Cite

Mayer-Eichberger, V. (2015). Just-in-Time Hierarchical Constraint Decomposition. Proceedings of the AAAI Conference on Artificial Intelligence, 29(1). https://doi.org/10.1609/aaai.v29i1.9733