Algorithms for computing or approximating optimal decompositions for decompositional parameters such as treewidth or clique-width have so far traditionally been tailored to specific width parameters. Moreover, for mim-width, no efficient algorithms for computing good decompositions were known, even under highly restrictive parameterizations. In this work we identify F-branchwidth as a class of generic decompositional parameters that can capture mim-width, treewidth, clique-width as well as other measures. We show that while there is an infinite number of F-branchwidth parameters, only a handful of these are asymptotically distinct. We then develop fixed-parameter and kernelization algorithms (under several structural parameterizations) that can compute every possible F-branchwidth, providing a unifying framework that can efficiently obtain near-optimal tree-decompositions, k-expressions, as well as optimal mim-width decompositions.
翻译:计算或接近优化分解参数的最佳分解分解参数(如树枝或环形)的算法,传统上一直是根据特定的宽度参数量身定制的。此外,对于 mim- width 来说,即使在高度限制性参数化的情况下,计算良好分解的算法也不为人知。 在这项工作中,我们确定F- branchwid 是一类通用分解参数,可以捕捉 mim- width、 树枝、 crique-width 及其他措施。 我们显示,虽然有无限数量的F- branchwids 参数,但其中只有少数参数是同质的。 我们随后开发了固定的参数和内核分解算法(在几种结构参数化下),可以对每一种可能的F- branchwidth进行分解算,提供一个统一框架,可以有效地获取近最佳的树分解位置、 k- 和最佳的mim- with 分解位置。