NEW WORST-CASE UPPER BOUND FOR COUNTING EXACT SATISFIABILITY

被引：1
|
作者：
Zhou, Junping [1 ]
Su, Weihua [1 ]
Wang, Jianan [1 ]
机构：
[1] NE Normal Univ, Sch Comp Sci, Changchun 130117, Peoples R China
来源：
INTERNATIONAL JOURNAL OF FOUNDATIONS OF COMPUTER SCIENCE | 2014年 / 25卷 / 06期
基金：
中国国家自然科学基金;
关键词：
#XSAT; upper bound; resolution principle; common literals principle; RANDOM CONSTRAINT SATISFACTION; ALGORITHMS; KNAPSACK;
D O I：
10.1142/S0129054114500270
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
The counting exact satisfiablity problem (#XSAT) is a problem that computes the number of truth assignments satisfying only one literal in each clause. This paper presents an algorithm that solves the #XSAT problem in O(1.1995(n)), which is faster than the best algorithm running in O(1.2190(n)), where n denotes the number of variables. To increase the efficiency of the algorithm, a new principle, called common literals principle, is addressed to simplify formulae. This allows us to further eliminate literals. In addition, we firstly apply the resolution principles into solving #XSAT problem, and therefore it improves the efficiency of the algorithm further.
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页码：667 / 678
页数：12
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