论文标题
连通性约束的平衡皇冠分解
Balanced Crown Decomposition for Connectivity Constraints
论文作者
论文摘要
我们介绍了平衡的皇冠分解,该分解捕获了其连接的特定大小的诱导子图所施加的结构。此类子图是在各个应用领域中流行的建模工具,在该领域,连通性条件的非本地性质通常会导致非常具有挑战性的算法任务。平衡的皇冠分解是冠状分解和平衡分区的组合,它适用于图形编辑以及图形包装和分区问题。我们通过得出各种此类问题的改进的内核化和近似算法来说明这一点。特别是,通过这种结构,我们获得了平衡连接分区(BCP)问题的第一个恒定因子近似,其中任务是将顶点加权图划分为$ k $连接的组件,其重量大致相等。我们为两个最常用的目标得出了一个3-轴向化,以最大程度地提高最轻的组件的重量或最大程度地减少最重的组件的重量。
We introduce the balanced crown decomposition that captures the structure imposed on graphs by their connected induced subgraphs of a given size. Such subgraphs are a popular modeling tool in various application areas, where the non-local nature of the connectivity condition usually results in very challenging algorithmic tasks. The balanced crown decomposition is a combination of a crown decomposition and a balanced partition which makes it applicable to graph editing as well as graph packing and partitioning problems. We illustrate this by deriving improved kernelization and approximation algorithms for a variety of such problems. In particular, through this structure, we obtain the first constant-factor approximation for the Balanced Connected Partition (BCP) problem, where the task is to partition a vertex-weighted graph into $k$ connected components of approximately equal weight. We derive a 3-approximation for the two most commonly used objectives of maximizing the weight of the lightest component or minimizing the weight of the heaviest component.