We consider a variant of treewidth that we call clique-partitioned treewidth in which each bag is partitioned into cliques. This is motivated by the recent development of FPT-algorithms based on similar parameters for various problems. With this paper, we take a first step towards computing clique-partitioned tree decompositions. Our focus lies on the subproblem of computing clique partitions, i.e., for each bag of a given tree decomposition, we compute an optimal partition of the induced subgraph into cliques. The goal here is to minimize the product of the clique sizes (plus 1). We show that this problem is NP-hard. We also describe four heuristic approaches as well as an exact branch-and-bound algorithm. Our evaluation shows that the branch-and-bound solver is sufficiently efficient to serve as a good baseline. Moreover, our heuristics yield solutions close to the optimum. As a bonus, our algorithms allow us to compute first upper bounds for the clique-partitioned treewidth of real-world networks. A comparison to traditional treewidth indicates that clique-partitioned treewidth is a promising parameter for graphs with high clustering.
翻译:我们考虑的是树枝的变种,我们把每袋树枝都称为分层树枝,其中每个包被分割成碎屑。这是最近根据各种问题的类似参数开发的FPT-algorithm的产物(+1)所推动的。我们用这份文件,我们迈出了计算分层树分解的最初一步。我们把注意力放在计算分层分区的副问题上,即,对于每袋特定树分解,我们计算出一个最佳的分层分层。我们计算出一个最佳的分层分层分层。我们的目标是最大限度地减少分层大小(+1)的产物。我们展示了这个问题的硬性。我们还描述了四种高超度方法以及精确的分层和分层算法。我们的评估表明,分层解器足够有效,可以用作良好的基准。此外,对于每袋树枝分层分层分层分层的解决方案接近最佳的解决方案。作为奖励,我们的算法使我们能够将首层分层分层的分层分层,用于传统-分层的树形结构图图图的对比。