Title: More efficient two-mode stochastic local search for random 3-satisfiability
Author: Luo, Chuan (1)
; Su, Kaile (2)
; Cai, Shaowei (3)
Corresponding Author: Luo, C.(chuanluosaber@gmail.com)
Keyword: Local search
; Satisfiability
; Linear combination
; Greedy
; Diversification
; Property
Source: Applied Intelligence
Issued Date: 2014
Volume: 41, Issue: 3, Pages: 665-680 Indexed Type: SCI
; EI
Department: (1) Key Laboratory of High Confidence Software Technologies of Ministry of Education, Peking University, Beijing, China; (2) Institute for Integrated and Intelligent Systems, Griffith University, Brisbane, Australia; (3) State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing, China; (4) Queensland Research Laboratory, NICTA, Brisbane, Australia
Abstract: Stochastic local search (SLS) is a popular paradigm in incomplete solving for the Boolean satisfiability problem (SAT). Most SLS solvers for SAT switch between two modes, i.e., the greedy (intensification) mode and the diversification mode. However, the performance of these two-mode SLS algorithms lags far behind on solving random 3-satisfiability (3-SAT) problem, which is a significant special case of the SAT problem. In this paper, we propose a new hybrid scoring function called MC based on a linear combination of a greedy property make and a diversification property ConfTimes, and then utilize MC to develop a new two-mode SLS solver called CCMC. To evaluate the performance of CCMC, we conduct extensive experiments to compare CCMC with five state-of-the-art two-mode SLS solvers (i.e., Sparrow2011, Sattime2011, EagleUP, gNovelty+PCL and CCASat) on a broad range of random 3-SAT instances, including all large 3-SAT ones from SAT Competition 2009 and SAT Competition 2011 as well as 200 generated satisfiable huge random 3-SAT ones. The experiments illustrate that CCMC obviously outperforms its competitors, indicating the effectiveness of CCMC. We also analyze the effectiveness of the underlying ideas in CCMC and further improve the performance of CCMC on solving random 5-SAT instances. © 2014 Springer Science+Business Media New York. English Abstract: Stochastic local search (SLS) is a popular paradigm in incomplete solving for the Boolean satisfiability problem (SAT). Most SLS solvers for SAT switch between two modes, i.e., the greedy (intensification) mode and the diversification mode. However, the performance of these two-mode SLS algorithms lags far behind on solving random 3-satisfiability (3-SAT) problem, which is a significant special case of the SAT problem. In this paper, we propose a new hybrid scoring function called MC based on a linear combination of a greedy property make and a diversification property ConfTimes, and then utilize MC to develop a new two-mode SLS solver called CCMC. To evaluate the performance of CCMC, we conduct extensive experiments to compare CCMC with five state-of-the-art two-mode SLS solvers (i.e., Sparrow2011, Sattime2011, EagleUP, gNovelty+PCL and CCASat) on a broad range of random 3-SAT instances, including all large 3-SAT ones from SAT Competition 2009 and SAT Competition 2011 as well as 200 generated satisfiable huge random 3-SAT ones. The experiments illustrate that CCMC obviously outperforms its competitors, indicating the effectiveness of CCMC. We also analyze the effectiveness of the underlying ideas in CCMC and further improve the performance of CCMC on solving random 5-SAT instances. © 2014 Springer Science+Business Media New York. Language: 英语
WOS ID: WOS:000342426700001
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Content Type: 期刊论文
URI: http://ir.iscas.ac.cn/handle/311060/16809
Appears in Collections: 软件所图书馆_期刊论文
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Recommended Citation:
Luo, Chuan ,Su, Kaile ,Cai, Shaowei . More efficient two-mode stochastic local search for random 3-satisfiability[J]. Applied Intelligence,2014-01-01,41(3):665-680.
