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Generating Instances for MAX2SAT with Optimal Solutions

机译:使用最佳解决方案生成MAX2SAT的实例

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摘要

A test instance generator (an instance generator for short) for MAX2SAT is a procedure that produces, given a number n of variables, a 2-CNF formula F of n variables (randomly chosen from some reasonably large domain), and simultaneously provides one of the optimal solutions for F. We propose an outline to design an instance generator using an expanding graph of a certain type, called here an "exact 1/2-enlarger". We first show a simple algorithm for constructing an exact 1/2-enlarger, thereby deriving one concrete polynomial-time instance generator GEN. We also show that an exact 1/2-enlarger can be obtained with high probability from graphs randomly constructed. From this fact, we propose another type of instance generator RGEN; it produces a 2-CNF formula with a solution which is optimal for the formula with high probability. However, RGEN produces less structured formulas and a much larger class of formulas than GEN. In fact, we prove the NP-hardness of MAX2SAT over the set of 2-CNF formulas produced by RGEN.
机译:MAX2SAT的测试实例生成器(简称为实例生成器)是这样的过程:在给定数量n的变量的情况下,生成n个变量的2-CNF公式F(从某个合理的较大域中随机选择),并同时提供F的最佳解决方案。我们提出了一个轮廓,以使用某种类型的展开图(这里称为“精确1/2放大”)设计实例生成器。我们首先展示一个简单的算法,用于构造一个精确的1/2放大倍数,从而推导一个具体的多项式时间实例生成器GEN。我们还表明,可以从随机构造的图形中以较高的概率获得精确的1/2放大倍数。基于这一事实,我们提出了另一种类型的实例生成器RGEN。它生成具有解决方案的2-CNF公式,该公式对于概率很高的公式是最佳的。但是,与GEN相比,RGEN产生的结构化公式较少,而公式类别更大。实际上,我们证明了RGEN生成的2-CNF公式集上MAX2SAT的NP硬度。

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