{"type":"ScholarlyArticle","title":"From Decimation to Local Search and Back: A New Approach to MaxSAT","authors":[{"name":"Shaowei Cai","slug":"shaowei-cai","given":"Shaowei","family":"Cai","affiliation":"State Key Laboratory of Computer Science , Institute of Software , Chinese Academy of Sciences , China; School of Computer and Control Engineering , University of Chinese Academy of Sciences , China"},{"name":"Chuan Luo","slug":"chuan-luo","given":"Chuan","family":"Luo","affiliation":"Institute of Computing Technology , Chinese Academy of Sciences , China"},{"name":"Haochen Zhang","slug":"haochen-zhang","given":"Haochen","family":"Zhang","affiliation":"State Key Laboratory of Computer Science , Institute of Software , Chinese Academy of Sciences , China"}],"abstract":"Maximum Satisfiability (MaxSAT) is an important NP-hard combinatorial optimization problem with many applications and MaxSAT solving has attracted much interest. This work proposes a new incomplete approach to MaxSAT. We propose a novel decimation algorithm for MaxSAT, and then combine it with a local search algorithm. Our approach works by interleaving between the decimation algorithm and the local search algorithm, with useful information passed between them. Experiments show that our solver DeciLS achieves state of the art performance on all unweighted benchmarks from the MaxSAT Evaluation 2016. Moreover, compared to SAT-based MaxSAT solvers which dominate industrial benchmarks for years, it performs better on industrial benchmarks and significantly better on application formulas from SAT Competition. We also extend this approach to (Weighted) Partial MaxSAT, and the resulting solvers significantly improve local search solvers on crafted and industrial benchmarks, and are complementary (better on WPMS crafted benchmarks) to SAT-based solvers.","doi":"10.24963/ijcai.2017/80","url":"https://ijcai.org/proceedings/2017/80","pdf":"https://ijcai.org/proceedings/2017/0080.pdf","markdown":"https://ijcai.org/proceedings/2017/80.md","bibtex":"https://ijcai.org/proceedings/2017/bibtex/80","volume":{"slug":"2017","title":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2017","url":"https://ijcai.org/proceedings/2017/","year":2017,"location":"Melbourne, Australia","dates":"19-25 August 2017","editors":"Carles Sierra","isbn":"978-0-9992411-0-3","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2017"},"section":"Constraints and Satisfiability","track":"Main track","number":80,"pages":{"first":571,"last":577},"keywords":["Combinatorial & Heuristic Search: Combinatorial search/optimisation","Constraints and Satisfiability: MaxSAT, MinSAT"],"videos":[],"references":[{"position":1,"raw":"[Altarelli et al., 2009] Fabrizio Altarelli, Rémi Monasson, Guilhem Semerjian, and Francesco Zamponi. 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