Elsevier

Artificial Intelligence

Volume 235, June 2016, Pages 26-39
Artificial Intelligence

MaxSAT by improved instance-specific algorithm configuration,☆☆

https://doi.org/10.1016/j.artint.2015.12.006Get rights and content
Under an Elsevier user license
open archive

Abstract

Our objective is to boost the state-of-the-art performance in MaxSAT solving. To this end, we employ the instance-specific algorithm configurator ISAC, and improve it with the latest in portfolio technology. Experimental results on SAT show that this combination marks a significant step forward in our ability to tune algorithms instance-specifically. We then apply the new methodology to a number of MaxSAT problem domains and show that the resulting solvers consistently outperform the best existing solvers on the respective problem families. In fact, the solvers presented here were independently evaluated at the 2013 and 2014 MaxSAT Evaluations where they won several categories.

Keywords

Algorithm configuration
Algorithm selection
MaxSAT

Cited by (0)

This paper was submitted to the Competition Section of the journal.

☆☆

Research partially supported by the Ministerio de Economía y Competividad research project TASSAT2: TIN2013-48031-C4-4-P.