Efficient Tough Random Symmetric 3-SAT Generator

R. Amador, Chen-Fu Chiang, Chang-Yu Hsieh
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Abstract

We designed and implemented an efficient tough random symmetric 3-SAT generator and propose two deterministic algorithms that efficiently generate 3-SAT instances with a unique solution. We quantify the first algorithms hardness in terms of CPU time, numbers of restarts, decisions, propagations, conflicts and conflicted literals that occur when a solver tries to solve 3-SAT instances. In this experiment, the clause variable ratio was chosen to be around the conventional critical phase transition number 4.24. The experiment shows that instances generated by our generator are significantly harder than instances generated by the Tough K-SAT generator. The two deterministic algorithms generate 3-SAT instances with the number of clauses scaling as 4n, where n is the number of variables, and (n+6), respectively. By combining these two algorithms along with a simple padding algorithm, we prove a hybrid algorithm that can generate n-variable instances with the number of clauses that scale between (n+6) and 7n(n-1)(n-2). Overall, all proposed SAT generators seek to explore unique difficult to solve SAT problems.
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高效硬随机对称3-SAT发生器
我们设计并实现了一个高效的硬随机对称3-SAT生成器,并提出了两种确定性算法,可以有效地生成具有唯一解的3-SAT实例。当求解器试图解决3-SAT实例时,我们根据CPU时间、重启次数、决策、传播、冲突和冲突字面量来量化第一种算法的硬度。在本实验中,子句变比选择在常规临界相变数4.24附近。实验表明,我们的生成器生成的实例比Tough K-SAT生成器生成的实例要困难得多。这两种确定性算法生成的3-SAT实例的子句数缩放为4n,其中n为变量数,(n+6)。通过将这两种算法与一个简单的填充算法结合起来,我们证明了一种混合算法,它可以生成n个变量实例,子句的数量在(n+6)和7n(n-1)(n-2)之间。总的来说,所有提出的SAT发生器寻求探索独特的难以解决的SAT问题。
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