Local Search with Configuration Checking for SAT

被引:27
作者
Cai, Shaowei [1 ]
Su, Kaile [2 ]
机构
[1] Peking Univ, Minist Educ, Key Lab High Confidence Software Technol, Beijing 100871, Peoples R China
[2] Griffith Univ, Inst Integrated & Intelligent Syst, Brisbane, Qld, Australia
来源
2011 23RD IEEE INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI 2011) | 2011年
基金
澳大利亚研究理事会; 中国国家自然科学基金;
关键词
SAT; Local Search; Configuration Checking;
D O I
10.1109/ICTAI.2011.18
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Local Search is an appealing method for solving the Boolean Satisfiability problem (SAT). However, this method suffers from the cycling problem which severely limits its power. Recently, a new strategy called configuration checking (CC) was proposed, for handling the cycling problem in local search. The CC strategy was used to improve a state-of-the-art local search algorithm for Minimum Vertex Cover. In this paper, we propose a novel local search strategy for the satisfiability problem, i.e., the CC strategy for SAT. The CC strategy for SAT takes into account the circumstances of the variables when selecting a variable to flip, where the circumstance of a variable refers to truth values of all its neighboring variables. We then apply it to design a local search algorithm for SAT called SWcc (Smoothed Weighting with Configuration Checking). Experimental results show that the CC strategy for SAT is more efficient than the previous strategy for handling the cycling problem called tabu. Moreover, SWcc significantly outperforms the best local search SAT solver in SAT Competition 2009 called TNM on large random 3-SAT instances.
引用
收藏
页码:59 / 66
页数:8
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