不同紧度下约束满足问题的相变现象

提出了一个基于RB模型的随机约束满足问题即◢p◣-RB模型。该模型考虑了约束紧度的多样性,将所有约束按照不同的权重分成若干组,同一组具有相同的约束紧度,而相异组具有不同的约束紧度。用二阶矩方法严格证明了随着控制参数的不断增加,◢p◣-RB模型发生了精确的可满足性相变现象。数值实验表明该模型的有解概率经历了从1到0的突然转变,同时求解难度在相变区域达到高峰,表明该模型在相变区域能产生大量的难解实例。     

两种改进的模拟退火算法求解大值域约束满足问题

随机约束满足问题的相变现象及求解算法是NP-完全问题的研究热点。RB模型（Revised B）是一个非平凡的随机约束满足问题,它具有精确的可满足性相变现象和极易产生难解实例这两个重要特征。针对RB模型这一类具有大值域的随机约束满足问题,提出了两种基于模拟退火的改进算法即RSA（Revised Simulated Annealing Algorithm）和GSA（Genetic-simulated Annealing Algorithm）。将这两种算法用于求解RB模型的随机实例,数值实验结果表明：在进入相变区域时,RSA和GSA算法依然可以有效地找到随机实例的解,并且在求解效率上明显优于随机游走算法。在接近相变阈值点时,由这两种算法得到的最优解仅使得极少数的约束无法满足。     

一种基于变量熵求解约束满足问题的置信传播算法

在置信传播(belief propagation,BP)算法中,提出一种基于变量熵来挑选变量从而固定变量赋值的策略,用于求解一类具有增长定义域的随机约束满足问题.RB模型是一个具有增长定义域的随机约束满足问题的典型代表,已经严格证明它不仅存在精确的可满足性相变现象,而且可以生成难解实例.在RB模型上选取两组不同的参数进行数值实验.结果表明:在接近可满足性相变点时,BP引导的消去算法仍然可以非常有效地找到随机实例的解;不断增加问题的规模,算法的运行时间呈指数级增长;并且当控制参数(约束紧度)增加时,变量的平均自由度逐渐降低.     

随机可满足实例集上警示传播算法的收敛性

信息传播算法在求解随机kSAT问题时有惊人的效果,难解区域变窄.对于这种现象,至今缺少系统的理论解释.警示传播(warning propagation,简称WP)算法是一种基础的信息传播算法,为有效分析WP算法在随机kCNF公式上的收敛性,给出了随机kCNF公式因子图上圈存在的相变点.在随机kCNF公式产生模型G(n,k,p)中,取k=3,p=d/n2,因子图中圈存在的相变点为p=1/8n2.当d＜1/8时,因子图中开始出现圈,且每个连通分支至多有一个圈,因子图中含圈的连通分支的数目以及圈的长度均与n无关.因此,因子图是由森林和一些含有唯一圈的连通分支构成.证明了WP算法在这些实例集上高概率收敛,并且给出了算法的迭代步数为O(logn+s),其中,s为连通分支的大小.     

用吴方法求解可满足性问题(Ⅱ)--实验研究

本文使用随机3-SAT实例模型,对算法变换思想指导下设计的吴方法求解可满足性问题的算法进行了实验,并与语义归结、支持集归结和DP算法进行了对比.     

随机约束满足问题相变研究综述

随机约束满足问题是经典的NP完全问题,在理论研究和现实生活中有着广泛应用。研究人员发现随机约束满足问题存在相变现象,近几十年来关于此问题相变的研究成果不断涌现。从随机图着色问题和随机可满足问题2个最经典的随机约束满足问题入手,从算法研究、理论物理和数学证明3个方面综述了随机图着色问题和随机可满足问题的相变研究成果。最后对随机约束满足问题相变的研究趋势进行了展望。     

规则实例集上警示传播算法的收敛性

信息传播算法求解随机3-SAT问题时非常有效,能使难解区域变窄.然而,对于因子图带有环的实例,信息传播算法并不总有效,常表现为不收敛.对于这种现象,至今缺少系统的理论解释.警示传播(Warning Propagation,WP)算法是一种基础的信息传播算法,对WP算法的收敛性研究是其它信息传播算法收敛性研究的重要基础.将一个3-SAT问题转换为具有规则结构的(3,4)-SAT问题,(3,4)-SAT问题是NP-完全的.基于(3,4)-SAT问题的规则结构性质,分析WP算法的收敛性.选取了3组不同规模的实例进行实验模拟,结果表明:在这种规则结构的可满足性实例集上,WP算法的收敛性有较大提高.     

约束可满足性中求解RB模型实例的算法综述

约束满足问题是人工智能领域中最基本的NP完全问题之一。多年来,随着约束满足问题的深入研究,国内外学者提出多种实例模型。其中,RB模型是一种能生成具有精确相变的增长域约束满足问题实例,其求解难度极具挑战性。为了寻找其求解的新型高效算法,促进约束可满足问题的RB模型求解算法领域的研究,首先从约束满足问题的模型发展、求解技术进行分析;其次,对各类求解RB模型实例算法进行梳理,将求解的算法文献划分为回溯启发式类、信息传播类和元启发式类相关改进算法,从算法原理、改进策略、收敛性和精确度等方面进行对比综述;最后给出求解RB模型实例算法的研究趋势和发展方向。     

求解多文字可满足SAT问题的置信传播算法

可满足(SAT)问题是指:是否存在一组布尔变元赋值,使得合取范式公式中每个子句至少有一个文字为真.多文字可满足SAT问题是指:是否存在一组布尔变元赋值,使得CNF公式中每个子句至少有两个文字为真.显然,此问题仍然是一个NP难问题.为了研究解决多文字可满足SAT问题的算法,引入随机实例产生模型,设计求解多文字可满足SAT问题的置信传播算法.最后,用实例模型产生了大量数据进行实验验证,结果表明:该算法求解多文字可满足SAT问题的性能优于其他启发式算法.     

用吴方法求解可满足性问题(Ⅰ)--算法变换

本文在算法变换的思想指导下,研究了用吴方法求解可满足性问题的特点.通过建立吴方法的基本操作与子句间有限制的归结操作的对应,证明了吴方法求解可满足性问题基本上是一种以特征列计算为核心的有限制的子句归结过程,不仅使吴方法和归结法相互引入新的概念和认识,而且在算法实现时可以避免复杂的多项式计算,同时可以更好地利用问题特性和已有经验以获得更高的效率.     

Easy problems are sometimes hard

We present a detailed experimental investigation of the easy-hard-easy phase transition for randomly generated instances of satisfiability problems. Problems in the hard part of the phase transition have been extensively used for benchmarking satisfiability algorithms. This study demonstrates that problem classes and regions of the phase transition previously thought to be easy can sometimes be orders of magnitude more difficult than the worst problems in problem classes and regions of the phase transition considered hard. These difficult problems are either hard unsatisfiable problems or are satisfiable problems which give a hard unsatisfiable subproblem following a wrong split. Whilst these hard unsatisfiable problems may have short proofs, these appear to be difficult to find, and other proofs are long and hard.     

Variable-Centered Consistency in Model RB

Model RB is a model of random constraint satisfaction problems, which exhibits exact satisfiability phase transition and many hard instances, both experimentally and theoretically. Benchmarks based on Model RB have been successfully used by various international algorithm competitions and many research papers. In a previous work, Xu and Li defined two notions called i-constraint assignment tuple and flawed i-constraint assignment tuple to show an exponential resolution complexity of Model RB. These two notions are similar to some kind of consistency in constraint satisfaction problems, but seem different from all kinds of consistency so far known in literatures. In this paper, we explicitly define this kind of consistency, called variable-centered consistency, and show an upper bound on a parameter in Model RB, such that up to this bound the typical instances of Model RB are variable-centered consistent.     

An explicit semidefinite characterization of satisfiability for Tseitin instances on toroidal grid graphs

This paper is concerned with the application of semidefinite programming to the satisfiability problem, and in particular with using semidefinite liftings to efficiently obtain proofs of unsatisfiability. We focus on the Tseitin satisfiability instances which are known to be hard for many proof systems. For Tseitin instances based on toroidal grid graphs, we present an explicit semidefinite programming problem with dimension linear in the size of the Tseitin instance, and prove that it characterizes the satisfiability of these instances, thus providing an explicit certificate of satisfiability or unsatisfiability. Research partially supported by the Natural Sciences and Engineering Research Council of Canada.     

Data reductions, fixed parameter tractability, and random weighted d-CNF satisfiability

Data reduction is a key technique in the study of fixed parameter algorithms. In the AI literature, pruning techniques based on simple and efficient-to-implement reduction rules also play a crucial role in the success of many industrial-strength solvers. Understanding the effectiveness and the applicability of data reduction as a technique for designing heuristics for intractable problems has been one of the main motivations in studying the phase transition of randomly-generated instances of NP-complete problems.In this paper, we take the initiative to study the power of data reductions in the context of random instances of a generic intractable parameterized problem, the weighted d-CNF satisfiability problem. We propose a non-trivial random model for the problem and study the probabilistic behavior of the random instances from the model. We design an algorithm based on data reduction and other algorithmic techniques and prove that the algorithm solves the random instances with high probability and in fixed-parameter polynomial time O(dknm) where n is the number of variables, m is the number of clauses, and k is the fixed parameter. We establish the exact threshold of the phase transition of the solution probability and show that in some region of the problem space, unsatisfiable random instances of the problem have parametric resolution proof of fixed-parameter polynomial size. Also discussed is a more general random model and the generalization of the results to the model.     

The satisfiability problem in regular CNF-formulas

 In this paper we deal with the propositional satisfiability (SAT) problem for a kind of multiple-valued clausal forms known as regular CNF-formulas and extend some known results from classical logic to this kind of formulas. We present a Davis–Putnam-style satisfiability checking procedure for regular CNF-formulas equipped with suitable data structures and prove its completeness. Then, we describe a series of experiments for regular random 3-SAT instances. We observe that, for the regular 3-SAT problem with this procedure, there exists a threshold of the ratio of clauses to variables such that (i) the most computationally difficult instances tend to be found near the threshold, (ii) there is a sharp transition from satisfiable to unsatisfiable instances at the threshold and (iii) the value of the threshold increases as the number of truth values considered increases. Instances in the hard part provide benchmarks for the evaluation of regular satisfiability solvers.     

Many hard examples in exact phase transitions

This paper analyzes the resolution complexity of two random constraint satisfaction problem (CSP) models (i.e. Model RB/RD) for which we can establish the existence of phase transitions and identify the threshold points exactly. By encoding CSPs into CNF formulas, it is proved that almost all instances of Model RB/RD have no tree-like resolution proofs of less than exponential size. Thus, we not only introduce new families of CSPs and CNF formulas hard to solve, which can be useful in the experimental evaluation of CSP and SAT algorithms, but also propose models with both many hard instances and exact phase transitions. Finally, conclusions are presented, as well as a detailed comparison of Model RB/RD with the Hamiltonian cycle problem and random 3-SAT, which, respectively, exhibit three different kinds of phase transition behavior in NP-complete problems.     

随机正则(k,r)-SAT问题的可满足临界

研究k-SAT问题实例中每个变元恰好出现r=2s次,且每个变元对应的正、负文字都出现s次的严格随机正则（k,r）-SAT问题.通过构造一个特殊的独立随机实验,结合一阶矩方法,给出了严格随机正则（k,r）-SAT问题可满足临界值的上界.由于严格正则情形与正则情形的可满足临界值近似相等,因此得到了随机正则（k,r）-SAT问题可满足临界值的新上界.该上界不仅小于当前已有的随机正则（k,r）-SAT问题的可满足临界值上界,而且还小于一般的随机k-SAT问题的可满足临界值.因此,这也从理论上解释了在相变点处的随机正则（k,r）-SAT问题实例通常比在相应相变点处同规模的随机k-SAT问题实例更难满足的原因.最后,数值分析结果验证了所给上界的正确性.     

取定s的严格d-正则随机(3,2s)-SAT问题的可满足临界

3-CNF公式的随机难解实例生成对于揭示3-SAT问题的难解实质和设计满足性测试的有效算法有着重要意义.对于整数k>2和s>0,如果在一个k-CNF公式中每个变量正负出现次数均为s,则称该公式是严格正则（k,2s）-CNF公式.受严格正则（k,2s）-CNF公式的结构特征启发,提出每个变量正负出现次数之差的绝对值均为d的严格d-正则（k,2s）-CNF公式,并使用新提出的SDRRK2S模型生成严格d-正则随机（k,2s）-CNF公式.取定整数5<s<11,模拟实验显示,严格d-正则随机（3,2s）-SAT问题存在SAT-UNSAT相变现象和HARD-EASY相变现象.因此,立足于3-CNF公式的随机难解实例生成,研究了严格d-正则随机（3,2s）-SAT问题在s取定时的可满足临界.通过构造一个特殊随机实验和使用一阶矩方法,得到了严格d-正则随机（3,2s）-SAT问题在s取定时可满足临界值的一个下界.模拟实验结果验证了理论证明所得下界的正确性.