随机k-XORSAT模型及其NP完全扩展中聚类与算法相变的关系
计算复杂性
2009-11-13 v2
摘要
我们研究了随机输入下唯一可扩展约束满足问题上的随机启发式搜索算法的性能。我们证明，对于任何保持底层实例泊松性质的启发式算法，（依赖于启发式的）搜索算法可能找到解的最大约束与变量比率，小于使解聚集并高度相关的临界比率。此外，我们证明，当每个约束的变量数k趋于无穷大时，所谓的广义单位子句启发式算法可以达到该聚类比率。
引用
@article{arxiv.0709.0367,
title = {Relationship between clustering and algorithmic phase transitions in the random k-XORSAT model and its NP-complete extensions},
author = {Fabrizio Altarelli and Remi Monasson and Francesco Zamponi},
journal= {arXiv preprint arXiv:0709.0367},
year = {2009}
}
评论
15 pages, 4 figures, Proceedings of the International Workshop on Statistical-Mechanical Informatics, September 16-19, 2007, Kyoto, Japan; some imprecisions in the previous version have been corrected