Amroun, Kamal

Habbas, Zineb

Singer, Daniel

Many real-world problems can be modelled as Constraint Satisfaction Problems (CSPs).
          Although CSP is NP-complete, it has been proved that non binary CSP instances may be
          efficiently solved if they are representable as Generalized Hypertree Decomposition (GHD)
          with small width. Algorithms for solving CSPs based on a GHD consider an extensional
          representation of constraints together with join and semi-join operations giving rise to
          new large constraint tables (or relations) needed to be temporarily saved. Extensional
          representation of constraints is quite natural and adapted to the specification of real
          problems but unfortunately limits significantly the practical performance of these
          algorithms. The present work tackles this problem using a compact representation of
          constraint tables. Consequently, to make algorithms compatible with this compact
          representation, new “compressed join” and “compressed semi-join” operations have to be
          defined. This last step constitutes our main contribution which, as far as we know, has
          never been presented. The correctness of this approach is proved and validated on multiple
          benchmarks. Experimental results show that using compressed relations and compressed
          operations improves significantly the practical performance of the basic algorithm
          proposed by Gottlob et al. for solving non binary CSPs with a Generalized
          Hypertree Decomposition

Zineb Habbas

Kamal Amroun

Daniel Singer

EDP Sciences OAI-PMH repository (1.2.0)

Generalized Hypertree Decomposition for solving non binary CSP
          with compressed table constraints

Numérisation de Documents Anciens Mathématiques

Generalized Hypertree Decomposition for solving non binary CSP with compressed table constraints

https://hal.archives-ouvertes.fr/hal-01277953

Generalized Hypertree Decomposition for solving non binary CSP with compressed table constraints

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EDP Sciences OAI-PMH repository (1.2.0)

Numérisation de Documents Anciens Mathématiques