Problem
Research questions and friction points this paper is trying to address.
(p, q)-Flexible Graph Connectivity
safe edges
minimum cost subset
graph G=(V, E)
approximation
A $(p+q)^{O(pq)}$-approximation for $(p, q)$-Flexible Graph Connectivity
🤖 AI Summary
本文针对(p,q)-灵活图连通性问题，提出了一种基于增广算法的$(p+q)^{O(pq)}$-近似解法，通过添加最少成本边集使图满足(p,q)连通要求。
📝 Abstract
In the $(p,q)$-Flexible Graph Connectivity problem, the input consists of non-negative integers $p$ and $q$ and a graph $G=(V, E)$ whose edges are classified into safe and unsafe edges with non-negative edge costs. A subgraph H of G is $(p,q)$-Flex-Connected if every non-empty proper subset of vertices has either at least $p$ safe edges or at least $p+q$ total edges crossing it. The goal is to find a minimum cost subset $F\subseteq E$ of edges such that the subgraph $(V, F)$ is $(p,q)$-Flex-Connected. We give a $(p+q)^{O(pq)}$-approximation for this problem, which in particular implies a constant approximation for every fixed constants $p$ and $q$. We achieve this by designing a $(p+q)^{O(pq)}$-approximation for the augmentation problem of finding a minimum cost subset of edges to add to make a (p,q-1)-Flex-Connected graph into a (p,q)-Flex-Connected graph. Underlying the augmentation algorithm is a structural result showing that all deficient cuts can be represented by min rooted-cuts in a $(p+q)^{pq}$-sized collection of digraphs. This structural result was discovered by ChatGPT Astra.
Innovation
Methods, ideas, or system contributions that make the work stand out.
(p,q)-Flexible Graph Connectivity
approximation algorithm
augmentation problem
deficient cuts
min rooted-cuts
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