For many problems, the important instances from practice possess certain structure that one should reflect in the design of specific algorithms. As data reduction is an important and inextricable part of today's computation, we employ one of the most successful models of such precomputation -- the kernelization. Within this framework, we focus on Traveling Salesperson Problem (TSP) and some of its generalizations. We provide a kernel for TSP with size polynomial in either the feedback edge set number or the size of a modulator to constant-sized components. For its generalizations, we also consider other structural parameters such as the vertex cover number and the size of a modulator to constant-sized paths. We complement our results from the negative side by showing that the existence of a polynomial-sized kernel with respect to the fractioning number, the combined parameter maximum degree and treewidth, and, in the case of Subset-TSP, modulator to disjoint cycles (i.e., the treewidth two graphs) is unlikely.
翻译:对于许多问题,实践中的重要实例都有一定的结构,在设计特定算法时应该反映出来。由于数据减少是今天计算的一个重要和不可分割的一部分,我们采用了最成功的这种预先计算模型之一 -- -- 内核化。在这个框架内,我们侧重于《旅行销售人问题》及其一些概括性。我们为TSP提供了一个内核,其尺寸为多数值,可以是反馈边缘数,也可以是固定尺寸组件的调制器大小。对于它的概括性,我们还考虑其他结构参数,如顶层覆盖数和调制器大小到固定尺寸路径。我们用负面来补充我们的结果,我们通过显示在分数、综合参数最大度和树宽度以及子-TSP的情况下,不可能存在混合参数的最大度和树宽度,以及就子-TSP而言,变形器变异周期(即树木两图)等。