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Combining Local Search and Backtracking Techniques for Constraint Satisfaction

机译:结合本地搜索和回溯技术来满足约束条件

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Backtracking techniques are well-known traditional methods for solving many constraint satisfaction problems (CSPs), including the satisfiability (SAT) problem in the propositional logic. In recent years, it has been reported that local search techniques are very effective in solving some large-scale instances of the SAT problem. In this research, we combine the backtracking and local search techniques into a single method for solving SAT and CSPs. When setting a parameter of the method to either of its two extreme values, we obtain the ordinary backtracking procedure or the local search procedure. For some problems, if the parameter takes values in the middle of the two extremes, the new method is much more effective than either backtracking or local search. We tested the method with classical problems like the n-Queens and random SAT instances, as well as some difficult problems from finite mathematics. In particular, using the new method, we solved four open problems in desikgn theory.
机译:回溯技术是解决许多约束满足问题(CSP)(包括命题逻辑中的可满足性(SAT)问题)的众所周知的传统方法。近年来,据报道,局部搜索技术在解决SAT问题的一些大规模实例方面非常有效。在这项研究中,我们将回溯和本地搜索技术结合为一种解决SAT和CSP的方法。将方法的参数设置为其两个极值中的任意一个时,我们将获得普通的回溯过程或本地搜索过程。对于某些问题,如果参数取两个极端值的中间值,则新方法比回溯或本地搜索要有效得多。我们用n-Queens和随机SAT实例等经典问题以及有限数学中的一些困难问题测试了该方法。特别是,使用新方法,我们解决了设计理论中的四个开放问题。

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