{"type":"ScholarlyArticle","title":"Rethinking the Soft Conflict Pseudo Boolean Constraint on MaxSAT Local Search Solvers","authors":[{"name":"Jiongzhi Zheng","slug":"jiongzhi-zheng","given":"Jiongzhi","family":"Zheng","affiliation":"School of Computer Science and Technology , Huazhong University of Science and Technology , China"},{"name":"Zhuo Chen","slug":"zhuo-chen","given":"Zhuo","family":"Chen","affiliation":"School of Computer Science and Technology , Huazhong University of Science and Technology , China"},{"name":"Chu-Min Li","slug":"chu-min-li","given":"Chu-Min","family":"Li","affiliation":"MIS , University of Picardie Jules Verne , France"},{"name":"Kun He","slug":"kun-he","given":"Kun","family":"He","affiliation":"School of Computer Science and Technology , Huazhong University of Science and Technology , China"}],"abstract":"MaxSAT is an optimization version of the famous NP-complete Satisfiability problem (SAT). Algorithms for MaxSAT mainly include complete solvers and local search incomplete solvers. In many complete solvers, once a better solution is found, a Soft conflict Pseudo Boolean (SPB) constraint will be generated to enforce the algorithm to find better solutions. In many local search algorithms, clause weighting is a key technique for effectively guiding the search directions. In this paper, we propose to transfer the SPB constraint into the clause weighting system of the local search method, leading the algorithm to better solutions. We further propose an adaptive clause weighting strategy that breaks the tradition of using constant values to adjust clause weights. Based on the above methods, we propose a new local search algorithm called SPB-MaxSAT that provides new perspectives for clause weighting on MaxSAT local search solvers. Extensive experiments demonstrate the excellent performance of the proposed methods.","doi":"10.24963/ijcai.2024/220","url":"https://ijcai.org/proceedings/2024/220","pdf":"https://ijcai.org/proceedings/2024/0220.pdf","markdown":"https://ijcai.org/proceedings/2024/220.md","bibtex":"https://ijcai.org/proceedings/2024/bibtex/220","volume":{"slug":"2024","title":"Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2024","url":"https://ijcai.org/proceedings/2024/","year":2024,"location":"Jeju, Korea","dates":"3-9 August 2024","editors":"Kate Larson","isbn":"978-1-956792-04-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2024"},"section":"Constraint Satisfaction and Optimization","track":"Main Track","number":220,"pages":{"first":1989,"last":1997},"keywords":["Constraint Satisfaction and Optimization: CSO: Satisfiabilty","Search: S: Local search","Constraint Satisfaction and Optimization: CSO: Solvers and tools"],"videos":[],"references":[{"position":1,"raw":"Benchmark #inst. 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