{"type":"ScholarlyArticle","title":"Combining Clause Learning and Branch and Bound for MaxSAT (Extended Abstract)","authors":[{"name":"Chu-Min Li","slug":"chu-min-li","given":"Chu-Min","family":"Li","affiliation":"Huazhong University of Science and Technology , Wuhan , China; Université de Picardie Jules Verne , Amiens , France; Aix Marseille Univ , Université de Toulon , CNRS , LIS , Marseille , France"},{"name":"Zhenxing Xu","slug":"zhenxing-xu","given":"Zhenxing","family":"Xu","affiliation":"Huazhong University of Science and Technology , Wuhan , China"},{"name":"Jordi Coll","slug":"jordi-coll","given":"Jordi","family":"Coll","affiliation":"Aix Marseille Univ , Université de Toulon , CNRS , LIS , Marseille , France"},{"name":"Felip Manyà","slug":"felip-manya","given":"Felip","family":"Manyà","affiliation":"Artificial Intelligence Research Institute (IIIA) , CSIC , Bellaterra , Spain"},{"name":"Djamal Habet","slug":"djamal-habet","given":"Djamal","family":"Habet","affiliation":"Aix Marseille Univ , Université de Toulon , CNRS , LIS , Marseille , France"},{"name":"Kun He","slug":"kun-he","given":"Kun","family":"He","affiliation":"Huazhong University of Science and Technology , Wuhan , China"}],"abstract":"Branch and Bound (BnB) has been successfully used to solve many combinatorial optimization problems. However, BnB MaxSAT solvers perform poorly when solving real-world and academic optimization problems. They are only competitive for random and some crafted instances. Thus, it is a prevailing opinion in the community that BnB is not really useful for practical MaxSAT solving.\r\nWe refute this opinion by presenting a new BnB MaxSAT solver, called MaxCDCL, which combines clause learning and an efficient bounding procedure. MaxCDCL is among the top 5 out of a total of 15 exact solvers that participated in the 2020 MaxSAT Evaluation, solving several instances that other solvers cannot solve. Furthermore, MaxCDCL solves the highest number of instances from different MaxSAT Evaluations when combined with the best existing solvers.","doi":"10.24963/ijcai.2022/739","url":"https://ijcai.org/proceedings/2022/739","pdf":"https://ijcai.org/proceedings/2022/0739.pdf","markdown":"https://ijcai.org/proceedings/2022/739.md","bibtex":"https://ijcai.org/proceedings/2022/bibtex/739","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":"Sister Conferences Best Papers","track":"Sister Conferences Best Papers","number":739,"pages":{"first":5299,"last":5303},"keywords":["Artificial Intelligence: General"],"videos":[{"label":"Video #1","url":"https://slideslive.com/38987256","length_sec":89,"provider":"slideslive"},{"label":"Video #2","url":"https://slideslive.com/38985399","length_sec":713,"provider":"slideslive"}],"references":[{"position":1,"raw":"[Abramé and Habet, 2014] André Abramé and Djamal Ha- bet. 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In Proceedings of Work- shop Pragmatics of SAT, POS-10, Edinburgh, UK, pages 15-27, 2010.","title":"Improved exact solver for the Weighted MAX-SAT problem","authors":"Adrian Kuegel","year":"2010","venue":"Proceedings of Workshop Pragmatics of SAT, POS-10","doi":null,"url":null,"internal_url":null},{"position":10,"raw":"[Li and Manyà, 2021] Chu Min Li and Felip Manyà. MaxSAT, hard and soft constraints. In Handbook of satis- fiability, second edition, pages 903-927. IOS Press, 2021.","title":"MaxSAT, hard and soft constraints","authors":"Min Chu, Felip Li, Manyà","year":"2021","venue":"Handbook of satisfiability","doi":null,"url":null,"internal_url":null},{"position":11,"raw":"[Li et al., 2005] Chu Min Li, Felip Manyà, and Jordi Planes. Exploiting unit propagation to compute lower bounds in branch and bound Max-SAT solvers. In Proceedings of CP 2005, volume 3709 of LNCS, pages 403-414. Springer, 2005.","title":"Exploiting unit propagation to compute lower bounds in branch and bound Max-SAT solvers","authors":"Min Chu, Felip Li, Jordi Manyà, Planes","year":"2005","venue":"Proceedings of CP 2005","doi":null,"url":null,"internal_url":null},{"position":12,"raw":"[Li et al., 2006] Chu Min Li, Felip Manyà, and Jordi Planes. Detecting disjoint inconsistent subformulas for computing lower bounds for Max-SAT. In Proceedings of AAAI 2006, pages 86-91, 2006.","title":"Detecting disjoint inconsistent subformulas for computing lower bounds for Max-SAT","authors":"Min Chu, Felip Li, Jordi Manyà, Planes","year":"2006","venue":"Proceedings of AAAI 2006","doi":null,"url":null,"internal_url":null},{"position":13,"raw":"[Li et al., 2007] Chu Min Li, Felip Manyà, and Jordi Planes. New inference rules for Max-SAT. Journal of Artificial Intelligence Research, 30:321-359, 2007.","title":"New inference rules for Max-SAT","authors":"Min Chu, Felip Li, Jordi Manyà, Planes","year":"2007","venue":"Journal of Artificial Intelligence Research","doi":null,"url":null,"internal_url":null},{"position":14,"raw":"[Li et al., 2009] Chu Min Li, Felip Manyà, Nouredine Ould Mohamedou, and Jordi Planes. Exploiting cycle structures in Max-SAT. In In Proceedings of SAT 2009, volume 5584 of LNCS, pages 467-480. Springer, 2009.","title":"Exploiting cycle structures in Max-SAT","authors":"Min Chu, Felip Li, Nouredine Manyà, Jordi Ould Mohamedou, Planes","year":"2009","venue":"Proceedings of SAT 2009","doi":null,"url":null,"internal_url":null},{"position":15,"raw":"[Li et al., 2010] Chu Min Li, Felip Manyà, Nouredine Ould Mohamedou, and Jordi Planes. Resolution-based lower bounds in MaxSAT. Constraints, 15(4):456-484, 2010.","title":"Resolution-based lower bounds in MaxSAT","authors":"Li","year":"2010","venue":"Constraints","doi":null,"url":null,"internal_url":null},{"position":16,"raw":"[Li et al., 2021] Chu-Min Li, Zhenxing Xu, Jordi Coll, Fe- lip Manyà, Djamal Habet, and Kun He. Combining clause learning and branch and bound for MaxSAT. In Proceed- ings of CP 2021, LIPIcs, pages 38:1-38:18, 2021.","title":"Combining clause learning and branch and bound for MaxSAT","authors":"Chu-Min Li, Zhenxing Xu, Jordi Coll, Felip Manyà, Djamal Habet, Kun He","year":"2021","venue":"Proceedings of CP 2021","doi":null,"url":null,"internal_url":null},{"position":17,"raw":"[Martins et al., 2014] Ruben Martins, Vasco M. Manquinho, and Inês Lynce. Open-WBO: A modular MaxSAT solver. In Proceedings of SAT 2014, volume 8561 of LNCS, pages 438-445. Springer, 2014.","title":"Open-WBO: A modular MaxSAT solver","authors":"Ruben Martins, M Vasco, Inês Manquinho, Lynce","year":"2014","venue":"Proceedings of SAT 2014","doi":null,"url":null,"internal_url":null},{"position":18,"raw":"[Piotrów, 2020] Marek Piotrów. UWrMaxSat: an efficient solver in MaxSAT evaluation 2020. MaxSAT Evaluation 2020, page 34, 2020.","title":"Marek Piotrów. UWrMaxSat: an efficient solver in MaxSAT evaluation 2020","authors":"Piotrów","year":"2020","venue":"MaxSAT Evaluation","doi":null,"url":null,"internal_url":null}],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}