IJCAI 2024poster3 citations

Rethinking the Soft Conflict Pseudo Boolean Constraint on MaxSAT Local Search Solvers

Jiongzhi Zheng, Zhuo Chen, Chu-Min Li, Kun He

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.

Constraint Satisfaction and Optimization: CSO: SatisfiabiltyConstraint Satisfaction and Optimization: CSO: Solvers and toolsSearch: S: Local search
BibTeX
@inproceedings{ijcai2024p220,
  title     = {Rethinking the Soft Conflict Pseudo Boolean Constraint on MaxSAT Local Search Solvers},
  author    = {Zheng, Jiongzhi and Chen, Zhuo and Li, Chu-Min and He, Kun},
  booktitle = {Proceedings of the Thirty-Third International Joint Conference on
               Artificial Intelligence, {IJCAI-24}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Kate Larson},
  pages     = {1989--1997},
  year      = {2024},
  month     = {8},
  note      = {Main Track},
  doi       = {10.24963/ijcai.2024/220},
  url       = {https://doi.org/10.24963/ijcai.2024/220},
}