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International Conference on Principles and Practice of Constraint Programming

CP 2020: Principles and Practice of Constraint Programming pp 90–106Cite as

Pure MaxSAT and Its Applications to Combinatorial Optimization via Linear Local Search

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Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 12333))

Abstract

Maximum Satisfiability (MaxSAT) is a general model for formulating combinatorial optimization problems. MaxSAT formulas encoded from different domains have different features, yet most MaxSAT solvers are designed for general formulas. This work considers an important subclass of MaxSAT, named as Pure MaxSAT, which characterizes a wide range of combinatorial optimization problems particularly subset problems. We design a novel local search method for Pure MaxSAT, which combines the idea of linear search and local search and is dubbed as linear local search. Our algorithm LinearLS significantly outperforms state of the art MaxSAT solvers on Pure MaxSAT instances, including instances from MaxSAT Evaluations and those encoded from three famous NP hard combinatorial optimization problems. Moreover, LinearLS outperforms state of the art algorithms for each tested combinatorial optimization problem on the popular benchmarks.

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Notes

  1. 1.

    To distinguish with the weight of soft clauses w(c) in the original formula, we use hw(c) to denote the hard clause weight introduced by our method.

  2. 2.

    ftp://dimacs.rutgers.edu/pub/challenges.

  3. 3.

    http://people.brunel.ac.uk/~mastjjb/jeb/orlib/files/.

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Acknowledgments

This work is partially supported by Youth Innovation Promotion Association of Chinese Academy of Sciences [No. 2017150] and Beijing Academy of Artificial Intelligence (BAAI).

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Authors and Affiliations

  1. State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing, China

    Shaowei Cai & Xindi Zhang

  2. School of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing, China

    Shaowei Cai & Xindi Zhang

Authors
  1. Shaowei Cai
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  2. Xindi Zhang
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Correspondence to Shaowei Cai .

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Editors and Affiliations

  1. Insight Centre for Data Analytics, School for Computer Science and Information Technology, University College Cork, Cork, Ireland

    Helmut Simonis

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Cai, S., Zhang, X. (2020). Pure MaxSAT and Its Applications to Combinatorial Optimization via Linear Local Search. In: Simonis, H. (eds) Principles and Practice of Constraint Programming. CP 2020. Lecture Notes in Computer Science(), vol 12333. Springer, Cham. https://doi.org/10.1007/978-3-030-58475-7_6

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  • DOI: https://doi.org/10.1007/978-3-030-58475-7_6

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