SUNNY

SUNNY: a lazy portfolio approach for constraint solving. Within the context of constraint solving, a portfolio approach allows one to exploit the synergy between different solvers in order to create a globally better solver. In this paper we present SUNNY: a simple and flexible algorithm that takes advantage of a portfolio of constraint solvers in order to compute -- without learning an explicit model -- a schedule of them for solving a given Constraint Satisfaction Problem (CSP). Motivated by the performance reached by SUNNY vs. different simulations of other state of the art approaches, we developed sunny-csp, an effective portfolio solver that exploits the underlying SUNNY algorithm in order to solve a given CSP. Empirical tests conducted on exhaustive benchmarks of MiniZinc models show that the actual performance of sunny-csp conforms to the predictions. This is encouraging both for improving the power of CSP portfolio solvers and for trying to export them to fields such as Answer Set Programming and Constraint Logic Programming.


References in zbMATH (referenced in 11 articles , 1 standard article )

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  1. Dantas, Augusto; Pozo, Aurora: On the use of fitness landscape features in meta-learning based algorithm selection for the quadratic assignment problem (2020)
  2. Lindauer, Marius; van Rijn, Jan N.; Kotthoff, Lars: The algorithm selection competitions 2015 and 2017 (2019)
  3. Nikolić, Mladen; Marinković, Vesna; Kovács, Zoltán; Janičić, Predrag: Portfolio theorem proving and prover runtime prediction for geometry (2019)
  4. Wang, Wenxi; Søndergaard, Harald; Stuckey, Peter J.: Wombit: a portfolio bit-vector solver using word-level propagation (2019)
  5. Amadini, Roberto; Gabbrielli, Maurizio; Mauro, Jacopo: SUNNY-CP and the MiniZinc challenge (2018)
  6. Amadini, Roberto; Gabbrielli, Maurizio; Mauro, Jacopo: Portfolio approaches for constraint optimization problems (2016)
  7. Audemard, Gilles; Simon, Laurent: Extreme cases in SAT problems (2016)
  8. Bischl, Bernd; Kerschke, Pascal; Kotthoff, Lars; Lindauer, Marius; Malitsky, Yuri; Fréchette, Alexandre; Hoos, Holger; Hutter, Frank; Leyton-Brown, Kevin; Tierney, Kevin; Vanschoren, Joaquin: ASlib: a benchmark library for algorithm selection (2016)
  9. Amadini, Roberto; Gabbrielli, Maurizio; Mauro, Jacopo: Why CP portfolio solvers are (under)utilized? Issues and challenges (2015)
  10. Björdal, Gustav; Monette, Jean-Noël; Flener, Pierre; Pearson, Justin: A constraint-based local search backend for MiniZinc (2015)
  11. Amadini, Roberto; Gabbrielli, Maurizio; Mauro, Jacopo: SUNNY: a lazy portfolio approach for constraint solving (2014)