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A Recursive Split, Solve, and Join Strategy for Solving Constraint Satisfaction Problems

机译:解决约束满足问题的递归拆分,求解和联接策略

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Constraint satisfaction is a recurrent problem found in both industrial and academic environments. The importance of this particular problem relies on the fact that many other problem domains can be represented as constraint satisfaction problems. The instances of this problem are usually difficult to solve due to their combinatorial nature, as they often require an exponential time in the number of variables. Various solving strategies have been proposed to tackle this problem in the past, being the two most important trends local search and backtracking-based methods. In this paper we propose a novel solving strategy that partitions constraint satisfaction instances into smaller ones that can be independently solved and later, uses their solutions to solve the original instance. This process is performed in a recursive fashion, including both a local search-based and a backtracking-based solver. Tests of the proposed approach on a set of benchmark instances taken from public repositories obtained encouraging results with respect to both local search and backtracking-based solvers applied in isolation.
机译:约束满意度是在工业和学术环境中都经常出现的问题。此特定问题的重要性取决于以下事实:许多其他问题域可以表示为约束满足问题。由于它们的组合性质,通常很难解决该问题的实例,因为它们通常需要变量数量成指数的时间。过去已经提出了各种解决方案来解决该问题,这是本地搜索和基于回溯的方法的两个最重要的趋势。在本文中,我们提出了一种新颖的求解策略,它将约束满足实例分解为较小的实例,这些实例可以独立求解,然后再使用它们的解决方案来求解原始实例。此过程以递归方式执行,包括基于本地搜索和基于回溯的求解器。对从公共存储库中获取的一组基准实例进行的拟议方法测试获得了令人鼓舞的结果,这些结果与本地搜索和孤立应用的基于回溯的求解器有关。

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