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Exploiting symmetries within constraint satisfaction search

机译:在约束满足搜索中利用对称性

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摘要

Symmetry often appears in real-world constraint satisfaction problems, but strategies for exploiting it are only beginning to be developed. Here, a framework for exploiting symmetry within depth--first search is proposed, leading to two heuristics for variable selection and a domain pruning procedure. These strategies are then applied to two highly symmetric combinatorial problems, namely the Ramsey problem and the generation of balanced incomplete block designs. Experimental results show that these general-purpose strategies can compete with, and in some cases outperform, previous more ad hoc procedures.
机译:对称性经常出现在现实世界中的约束满足问题中,但是利用它的策略才刚刚开始发展。在此,提出了一种利用深度内对称性的框架-首次搜索,从而导致了两种启发式选择变量和域修剪过程。然后将这些策略应用于两个高度对称的组合问题,即Ramsey问题和平衡不完整块设计的生成。实验结果表明,这些通用策略可以与以前的临时程序相竞争,并且在某些情况下可以胜过其他程序。

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