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Efficient local search for very large-scale satisfiability problems

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Jun GuAuthors Info & Claims

ACM SIGART Bulletin, Volume 3, Issue 1

Pages 8 - 12

https://doi.org/10.1145/130836.130837

Published: 01 January 1992 Publication History

Abstract

The satisfiability problem (SAT) is a fundamental problem in mathematical logic, inference, automated reasoning, and computing theory. In this correspondence, we report the results of applying local search techniques to solve the satisfiability problem. While a traditional resolution-based algorithm is not able to handle even moderately sized inference problems, a local search algorithm, tested through years of real program execution, is capable of computing very large-scale inference problems with fast, robust convergence. On a workstation computer, for example, it is able to solve a satisfiability problem with 50,000 clauses and 5,000 variables in a few seconds.

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He XMao WXu ZGu YHuang YZu ZWang LZhao MZou MBaeza-Yates RBonchi F(2024)An Efficient Local Search Algorithm for Large GD Advertising Inventory Allocation with Multilinear ConstraintsProceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3637528.3671811(1040-1049)Online publication date: 25-Aug-2024
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Bashir SKhattak A(2023)Private Web Search Using Proxy-Query Based Query Obfuscation SchemeIEEE Access10.1109/ACCESS.2023.323500011(3607-3625)Online publication date: 2023
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Gu JGu QDu D(2023)On optimizing the satisfiability (SAT) problemJournal of Computer Science and Technology10.1007/BF0295248214:1(1-17)Online publication date: 22-Mar-2023
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Index Terms

Efficient local search for very large-scale satisfiability problems
1. Computing methodologies
  1. Artificial intelligence
    1. Search methodologies
2. Theory of computation
  1. Design and analysis of algorithms
    1. Data structures design and analysis
      1. Sorting and searching

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Published In

cover image ACM SIGART Bulletin

ACM SIGART Bulletin Volume 3, Issue 1

Jan. 1992

37 pages

ISSN:0163-5719

DOI:10.1145/130836

Editor:
Lewis Johnson
USC/Information Sciences Institute, Marina del Rey, CA

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Copyright © 1992 Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 January 1992

Published in SIGAI Volume 3, Issue 1

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Cited By

He XMao WXu ZGu YHuang YZu ZWang LZhao MZou MBaeza-Yates RBonchi F(2024)An Efficient Local Search Algorithm for Large GD Advertising Inventory Allocation with Multilinear ConstraintsProceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3637528.3671811(1040-1049)Online publication date: 25-Aug-2024
https://dl.acm.org/doi/10.1145/3637528.3671811
Bashir SKhattak A(2023)Private Web Search Using Proxy-Query Based Query Obfuscation SchemeIEEE Access10.1109/ACCESS.2023.323500011(3607-3625)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3235000
Gu JGu QDu D(2023)On optimizing the satisfiability (SAT) problemJournal of Computer Science and Technology10.1007/BF0295248214:1(1-17)Online publication date: 22-Mar-2023
https://dl.acm.org/doi/10.1007/BF02952482
Alasow AJin PPerkowski M(2022)Quantum Algorithm for Variant Maximum SatisfiabilityEntropy10.3390/e2411161524:11(1615)Online publication date: 5-Nov-2022
https://doi.org/10.3390/e24111615
Alasow APerkowski M(2022)Quantum Algorithm for Maximum Satisfiability2022 IEEE 52nd International Symposium on Multiple-Valued Logic (ISMVL)10.1109/ISMVL52857.2022.00012(27-34)Online publication date: May-2022
https://doi.org/10.1109/ISMVL52857.2022.00012
Bashir SLai DMalik O(2022)Proxy-Terms Based Query Obfuscation Technique for Private Web SearchIEEE Access10.1109/ACCESS.2022.314992910(17845-17863)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3149929
Barotov DOsipov AKorchagin SPleshakova EMuzafarov DBarotov RSerdechnyy D(2021)Transformation Method for Solving System of Boolean Algebraic EquationsMathematics10.3390/math92432999:24(3299)Online publication date: 18-Dec-2021
https://doi.org/10.3390/math9243299
Alkasem HMenai M(2021)A Stochastic Local Search Algorithm for the Partial Max-SAT Problem Based on Adaptive Tuning and Variable Depth Neighborhood SearchIEEE Access10.1109/ACCESS.2021.30688249(49806-49843)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2021.3068824
AlKasem HMenai M(2020)Stochastic local search for Partial Max-SAT: an experimental evaluationArtificial Intelligence Review10.1007/s10462-020-09908-454:4(2525-2566)Online publication date: 26-Sep-2020
https://dl.acm.org/doi/10.1007/s10462-020-09908-4
Guerreiro ATerra-Neves MLynce IFigueira JManquinho V(2019)Constraint-Based Techniques in Stochastic Local Search MaxSAT SolvingPrinciples and Practice of Constraint Programming10.1007/978-3-030-30048-7_14(232-250)Online publication date: 30-Sep-2019
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