MaxSAT by improved instance-specific algorithm configuration

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 o...

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Bibliographic Details
Published inArtificial intelligence Vol. 235; pp. 26 - 39
Main Authors Ansótegui, Carlos, Gabàs, Joel, Malitsky, Yuri, Sellmann, Meinolf
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.06.2016
Subjects
Algorithm configuration
Algorithm selection
Algorithms
Artificial intelligence
Categories
Expert systems
MaxSAT
Methodology
Solvers
State of the art
Algorithm selection
MaxSAT
Algorithm configuration
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Summary: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.
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ISSN:0004-3702
1872-7921
DOI:10.1016/j.artint.2015.12.006