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关于 $M$-划分问题复杂性的研究

On the complexity of Sandwich Problems for $M$-partitions

Faculty of Mathematics and Physics, Charles University(查理大学数学与物理学院);Institut für Algebra, TU Dresden(德累斯顿工业大学代数研究所)

Alexey Barsukov, Santiago Guzmán-Pro

AI总结:

本文研究了$M$-划分问题的复杂性,通过结构分类和高效算法,对矩阵划分和沙丁鱼问题进行了P与NP完全的分类。

摘要:

我们对由反射性完全二色边图描述的约束满足问题(CSP)进行了结构分类。特别是,这种分类扩展了已知的图同态问题结构二分法,即Hell-Nešetřil定理(1990)。我们的分类也是高效的:我们可以用多项式时间检查反射性完全二色边图的CSP是否在P或NP完全中,而对于任意的二色边图,这一任务是NP完全的。然后,我们将主要结果应用于矩阵划分问题和沙丁鱼问题的上下文中。首先,我们获得了对一般矩阵划分问题类别的少数算法解决方案。其次,我们对矩阵划分的沙丁鱼问题进行了P与NP完全的分类。

英文摘要:

We present a structural classification of constraint satisfaction problems (CSP) described by reflexive complete $2$-edge-coloured graphs. In particular, this classification extends the structural dichotomy for graph homomorphism problems known as the Hell--Nešetřil theorem (1990). Our classification is also efficient: we can check in polynomial time whether the CSP of a reflexive complete $2$-edge-coloured graph is in P or NP-complete, whereas for arbitrary $2$-edge-coloured graphs, this task is NP-complete. We then apply our main result in the context of matrix partition problems and sandwich problems. Firstly, we obtain one of the few algorithmic solutions to general classes of matrix partition problems. And secondly, we present a P vs. NP-complete classification of sandwich problems for matrix partitions.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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