An Efficient Approach to Solving Random k-sat Problems

被引:0
|
作者
Gilles Dequen
Olivier Dubois
机构
[1] LaRIA,
[2] Université de Picardie Jules Verne,undefined
[3] LIP6,undefined
[4] CNRS-Université Paris 6,undefined
来源
关键词
satisfiability; solving; heuristic;
D O I
暂无
中图分类号
学科分类号
摘要
Proving that a propositional formula is contradictory or unsatisfiable is a fundamental task in automated reasoning. This task is coNP-complete. Efficient algorithms are therefore needed when formulae are hard to solve. Random \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$k-$\end{document}sat formulae provide a test-bed for algorithms because experiments that have become widely popular show clearly that these formulae are consistently difficult for any known algorithm. Moreover, the experiments show a critical value of the ratio of the number of clauses to the number of variables around which the formulae are the hardest on average. This critical value also corresponds to a ‘phase transition’ from solvability to unsolvability. The question of whether the formulae located around or above this critical value can efficiently be proved unsatisfiable on average (or even for a.e. formula) remains up to now one of the most challenging questions bearing on the design of new and more efficient algorithms. New insights into this question could indirectly benefit the solving of formulae coming from real-world problems, through a better understanding of some of the causes of problem hardness. In this paper we present a solving heuristic that we have developed, devoted essentially to proving the unsatisfiability of random \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$k-$\end{document}sat formulae and inspired by recent work in statistical physics. Results of experiments with this heuristic and its evaluation in two recent sat competitions have shown a substantial jump in the efficiency of solving hard, unsatisfiable random \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$k-$\end{document}sat formulae.
引用
收藏
页码:261 / 276
页数:15
相关论文
共 50 条
  • [1] An efficient approach to solving random k-SAT problems
    Dequen, Gilles
    Dubois, Olivier
    JOURNAL OF AUTOMATED REASONING, 2006, 37 (04) : 261 - 276
  • [2] An efficient approach to solving random k-sat problems
    Dequen, Gilles
    Dubois, Olivier
    Journal of Automated Reasoning, 2006, 37 (04): : 261 - 276
  • [3] The backtracking survey propagation algorithm for solving random K-SAT problems
    Raffaele Marino
    Giorgio Parisi
    Federico Ricci-Tersenghi
    Nature Communications, 7
  • [4] The backtracking survey propagation algorithm for solving random K-SAT problems
    Marino, Raffaele
    Parisi, Giorgio
    Ricci-Tersenghi, Federico
    NATURE COMMUNICATIONS, 2016, 7
  • [5] Solving k-SAT problems with generalized quantum measurement
    Zhang, Yipei
    Lewalle, Philippe
    Whaley, K. Birgitta
    arXiv,
  • [6] kcnfs:: An efficient solver for random k-SAT formulae
    Dequen, G
    Dubois, O
    THEORY AND APPLICATIONS OF SATISFIABILITY TESTING, 2004, 2919 : 486 - 501
  • [7] Polarised random k-SAT
    Danielsson, Joel Larsson
    Markstrom, Klas
    COMBINATORICS PROBABILITY AND COMPUTING, 2023, 32 (06) : 885 - 899
  • [8] Biased random k-SAT
    Larsson, Joel
    Markstrom, Klas
    RANDOM STRUCTURES & ALGORITHMS, 2021, 59 (02) : 238 - 266
  • [9] On an online random k-SAT model
    Kravitz, David
    RANDOM STRUCTURES & ALGORITHMS, 2008, 32 (01) : 115 - 124
  • [10] On the behaviour of random K-SAT on trees
    Krishnamurthy, Supriya
    Sumedha
    JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT, 2012,