Approximation Algorithms for Flexible Graph Connectivity
We present approximation algorithms for several network design problems in the model of Flexible Graph Connectivity (Adjiashvili, Hommelsheim and Mühlenthaler, "Flexible Graph Connectivity", Math. Program. pp. 1-33 (2021), and IPCO 2020: pp. 13-26). Let k≥ 1, p≥ 1 and q≥ 0 be integers. In an instance of the (p,q)-Flexible Graph Connectivity problem, denoted (p,q)-FGC, we have an undirected connected graph G = (V,E), a partition of E into a set of safe edges S and a set of unsafe edges U, and nonnegative costs c: E→ on the edges. A subset F ⊆ E of edges is feasible for the (p,q)-FGC problem if for any subset F' of unsafe edges with |F'|≤ q, the subgraph (V, F ∖ F') is p-edge connected. The algorithmic goal is to find a feasible solution F that minimizes c(F) = ∑_e ∈ F c_e. We present a simple 2-approximation algorithm for the (1,1)-FGC problem via a reduction to the minimum-cost rooted 2-arborescence problem. This improves on the 2.527-approximation algorithm of Adjiashvili et al. Our 2-approximation algorithm for the (1,1)-FGC problem extends to a (k+1)-approximation algorithm for the (1,k)-FGC problem. We present a 4-approximation algorithm for the (p,1)-FGC problem, and an O(qlog|V|)-approximation algorithm for the (p,q)-FGC problem. Finally, we improve on the result of Adjiashvili et al. for the unweighted (1,1)-FGC problem by presenting a 16/11-approximation algorithm. The (p,q)-FGC problem is related to the well-known Capacitated k-Connected Subgraph problem (denoted Cap-k-ECSS) that arises in the area of Capacitated Network Design. We give a min(k,2 u_max)-approximation algorithm for the Cap-k-ECSS problem, where u_max denotes the maximum capacity of an edge.
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