通过最远优先遍历燃烧图
Burning graphs through farthest-first traversal
摘要：
图燃烧问题是一个NP难的组合优化问题，它有助于量化图对传染的脆弱性。本文针对一般图上的这一问题，提出了一种简单的基于最远优先的近似算法。我们将此建议称为燃烧最远优先（BFF）算法。BFF以$O(n^3)$步长运行，近似因子为$3-2/b(G)$，其中$b(G)$是最优解的大小。尽管BFF很简单，但在一些基准数据集上测试时，它往往会生成接近最优的解决方案;事实上，它返回的解决方案与文献中更详细的算法返回的解决方案相似。
英文摘要：
The graph burning problem is an NP-hard combinatorial optimization problem that helps quantify the vulnerability of a graph to contagion. This paper introduces a simple farthest-first traversal-based approximation algorithm for this problem over general graphs. We refer to this proposal as the Burning Farthest-First (BFF) algorithm. BFF runs in $O(n^3)$ steps and has an approximation factor of $3-2/b(G)$, where $b(G)$ is the size of an optimal solution. Despite its simplicity, BFF tends to generate near-optimal solutions when tested over some benchmark datasets; in fact, it returns similar solutions to those returned by much more elaborated heuristics from the literature.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
