Affiliation:
1. University of Toronto
2. University of Helsinki
Abstract
Maximum satisfiability (MaxSAT) offers a competitive approach to solving NP-hard real-world optimization problems. While state-of-the-art MaxSAT
solvers rely heavily on Boolean satisfiability (SAT) solvers, a recent trend, brought on by MaxSAT solvers implementing the so-called implicit hitting
set (IHS) approach, is to integrate techniques from the realm of integer programming (IP) into the solving process. This allows for making use of additional
IP solving techniques to further speed up MaxSAT solving. In this line of work, we investigate the integration of the technique of reduced cost
fixing from the IP realm into IHS solvers, and empirically show that reduced cost fixing considerable speeds up a state-of-the-art MaxSAT solver implementing
the IHS approach.
Publisher
International Joint Conferences on Artificial Intelligence Organization
Cited by
1 articles.
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