One of the most elementary spreading models on graphs can be described by a fire spreading from a burning vertex in discrete time steps. At each step, all neighbors of burning vertices catch fire. A well-studied extension to model fire containment is to allow for fireproofing a number $B$ of non-burning vertices at each step. Interestingly, basic computational questions about this model are computationally hard even on trees. One of the most prominent such examples is Resource Minimization for Fire Containment (RMFC), which asks how small $B$ can be chosen so that a given subset of vertices will never catch fire. Despite recent progress on RMFC on trees, prior work left a significant gap in terms of its approximability. We close this gap by providing an optimal $2$-approximation and an asymptotic PTAS, resolving two open questions in the literature. Both results are obtained in a unified way, by first designing a PTAS for a smooth variant of RMFC, which is obtained through a careful LP-guided enumeration procedure. Moreover, we show that our new techniques, with several additional ingredients, carry over to the non-uniform $k$-center problem (NUkC), by exploiting a link between RMFC on trees and NUkC established by Chakrabarty, Goyal, and Krishnaswamy. This leads to the first approximation algorithm for NUkC that is optimal in terms of the number of additional centers that have to be opened.
翻译:图论中最基本的传播模型之一可以通过离散时间步长中燃烧顶点蔓延的火势来描述。在每个时间步,所有燃烧顶点的邻居都会着火。为模拟火势控制,一个经过深入研究的扩展模型允许在每个时间步对$B$个未燃烧顶点进行防火处理。值得注意的是,即使是在树结构上,关于该模型的基本计算问题在计算上也是困难的。其中最突出的例子是防火资源最小化问题,该问题探讨如何选择尽可能小的$B$值,使得给定顶点子集永远不会着火。尽管近期在树结构上的RMFC研究取得了进展,但先前工作在其近似性方面仍存在显著差距。我们通过提出最优的2-近似算法和渐近PTAS来弥补这一差距,从而解决了文献中的两个开放性问题。这两个结果均通过统一方法获得:首先为RMFC的平滑变体设计PTAS,该变体通过精细的线性规划引导枚举程序实现。此外,我们证明通过利用Chakrabarty、Goyal和Krishnaswamy建立的树结构RMFC与NUkC之间的联系,我们的新技术结合若干附加要素可推广至非均匀k中心问题。这为NUkC带来了首个在需额外开设中心数量方面达到最优的近似算法。