I am studying the following Weighted Forest Problem, which is an optimization problem in graph theory focused on finding optimal forest structures in robust scenarios. The problem is defined as follows:
Given an undirected graph $G = (V, E, w)$, where $V$ is the set of vertices, $E$ is the set of edges, and $w: E \rightarrow \mathbb{R}^+$ represents the edge weights. Let $\mathcal{F}$ be the family of all forests over $G$. The goal is to find a first-stage solution $S \subseteq \mathcal{F}$ that maximizes the following:
$$ \max_{S \in \mathcal{F}} \min_{D \subseteq E, |D| \leq k} \max_{R \subseteq E \setminus D, |R| \leq \ell} w((S \cup R) \setminus D) $$
Here, $D$ is the set of edges removed by an adversary, and $R$ is the set of edges re-added after removal.
So the problem consists of two stages:
- Stage One: You choose a forest $ S $.
- Stage Two:
- An adversary can remove up to $ k$ edges from your chosen forest. The set of removed edges is denoted by $ D $.
- You can then re-add up to $ \ell $ edges from the remaining edges in the graph. The set of re-added edges is denoted by $ R $.
- The final forest you end up with is $ (S \cup R) \setminus D $, and its total weight is $ w((S \cup R) \setminus D) $.
Your goal in the first stage is to choose a forest $ S $ such that, after the adversary’s worst-case removal and your subsequent recovery action, the weight of the final forest is as large as possible.
I would like to know if this problem is NP-hard. If so, could you please explain in detail how to prove that it is NP-hard or suggest some related reduction methods?
This figure is an example for k=2, l=1. The solid edge is the first stage solution and the red color edge is D. This example does not have R. And I would also like to know if this k=2, l=1 version problem is np-hard or not.