C.A. Micchelli, W.L. Miranker
Journal of the ACM
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 inde-pendently evaluated at the 2013 MaxSAT Evaluation where they won six of the eleven categories.
C.A. Micchelli, W.L. Miranker
Journal of the ACM
Saurabh Paul, Christos Boutsidis, et al.
JMLR
Joxan Jaffar
Journal of the ACM
Kenneth L. Clarkson, Elad Hazan, et al.
Journal of the ACM