{"type":"ScholarlyArticle","title":"Large Neighbourhood Search for Anytime MaxSAT Solving","authors":[{"name":"Randy Hickey","slug":"randy-hickey","given":"Randy","family":"Hickey","affiliation":"University of Toronto"},{"name":"Fahiem Bacchus","slug":"fahiem-bacchus","given":"Fahiem","family":"Bacchus","affiliation":"University of Toronto"}],"abstract":"Large Neighbourhood Search (LNS) is an algorithmic framework for optimization problems that can yield good performance in many domains. In this paper, we present a method for applying LNS to improve anytime maximum satisfiability (MaxSAT) solving by introducing a neighbourhood selection policy that shows good empirical performance. We show that our LNS solver can often improve the suboptimal solutions produced by other anytime MaxSAT solvers. When starting with a suboptimal solution of reasonable quality, our approach often finds a better solution than the original anytime solver can achieve. We demonstrate that implementing our LNS solver on top of three different state-of-the-art anytime solvers improves the anytime performance of all three solvers within the standard time limit used in the incomplete tracks of the annual MaxSAT Evaluation.","doi":"10.24963/ijcai.2022/253","url":"https://ijcai.org/proceedings/2022/253","pdf":"https://ijcai.org/proceedings/2022/0253.pdf","markdown":"https://ijcai.org/proceedings/2022/253.md","bibtex":"https://ijcai.org/proceedings/2022/bibtex/253","volume":{"slug":"2022","title":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2022","url":"https://ijcai.org/proceedings/2022/","year":2022,"location":"Vienna","dates":"23-29 July 2022","editors":"Luc De Raedt","isbn":"978-1-956792-00-3","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2022"},"section":"Constraint Satisfaction and Optimization","track":"Main Track","number":253,"pages":{"first":1818,"last":1824},"keywords":["Constraint Satisfaction and Optimization: Solvers and Tools","Constraint Satisfaction and Optimization: Satisfiabilty"],"videos":[{"label":"Video #1","url":"https://slideslive.com/38986852","length_sec":89,"provider":"slideslive"},{"label":"Video #2","url":"https://slideslive.com/38984995","length_sec":348,"provider":"slideslive"}],"references":[{"position":1,"raw":"[Bacchus et al., 2020a] Fahiem Bacchus, Jeremias Berg, Matti Järvisalo, and Rubens Martins. 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