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A universally fastest algorithm for Max 2-Sat, Max 2-CSP, and everything in between

机译:最大最快最快的最快算法,最大2-SAT,MAX 2-CSP以及之间的一切

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We introduce "hybrid" Max 2-CSP formulas consisting of "simple clauses", namely conjunctions and disjunctions of pairs of variables, and general 2-variable clauses, which can be any integer-valued functions of pairs of boolean variables. This allows an algorithm to use both efficient reductions specific to AND and OR clauses, and other powerful reductions that require the general CSP setting. Parametrizing an instance by the fraction p of non- simple clauses, we give an exact (exponential-time) algorithm that is the fastest polynomial-space algorithm known for Max 2-Sat (and other p = 0 formulas, with arbitrary mixtures of AND and OR clauses); the only efficient algorithm for mixtures of AND, OR, and general integer-valued clauses; and tied for fastest for general Max 2-CSP (p = 1). Since a pure 2-Sat input instance may be transformed to a general CSP instance in the course of being solved, the algorithm's efficiency and generality go hand in hand. Our novel analysis results in a family of running- time bounds, each optimized for a particular value of p. The algorithm uses new reductions introduced here, as well as recent reductions such as "clause-learning" and "2-reductions" adapted to our setting's mixture of simple and general clauses. Each reduction imposes constraints on various parameters, and the running-time bound is an "objective function" of these parameters and p. The optimal running-time bound is obtained by solving a convex nonlinear program, which can be done efficiently and with a certificate of optimality.
机译:我们引入由......组成“简单条款”,即连接词和双变量,和一般的2-可变条款的析取,其可以是对布尔变量的任何整值函数的“混合”最大2-CSP公式。这使得算法同时使用有效减少特定AND和OR子句,并要求普通CSP设置等强大的减少。通过非简单条款的p部分参数化的实例中,我们给出一个确切的(指数时间)算法,该算法是用于最多2 - 星期六(和另一个p = 0公式已知最快的多项式空间算法,用AND的任意混合物和OR子句);唯一有效的算法的和一般整数值条款混合物,OR,和;并列最快一般最多2-CSP(P = 1)。由于纯2至周六输入例如可以在被解决,算法的效率和普遍性齐头并进的过程中转化为一般的CSP实例。在一个家庭中运行 - 时间界限的本发明的新型的分析结果,每一个用于p的特定值进行了优化。该算法使用这里引入了新的削减,以及最近的折扣,如“条款的学习”,“两减”适用于简单和一般条款的我们的设置的混合物。每个减少强加各种参数约束,并且结合的运行时间是一个“目标函数”这些参数和P的。结合的最佳运行时间由求解凸非线性程序,它能够有效地和以最优的一个证书来完成获得。

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