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Faster algorithms for packing forests in graphs and related problems

Pavel Arkhipov, Vladimir Kolmogorov

TL;DR

This work advances the theory and practice of packing forests in graphs by developing a min–max framework for the bounded-indegree k-forest problem and an almost linear-time algorithm for τ = 0, enabling efficient solutions for related problems. It then leverages this foundation to achieve faster algorithms for the undirected k-forest problem and for directed and undirected edge-connectivity augmentation, using auxiliary graphs, pseudoforests, and top-clump contractions. The central innovations include a precise min–max characterization, a robust augmenting-path scheme, and a structured reduction to extensions and edge-splitting that collectively break prior complexity barriers. The results have practical implications for routing, rigidity analysis, and network design, offering scalable and deterministic methods for constructing large collections of edge-disjoint forests and for augmenting connectivity.

Abstract

We consider several problems related to packing forests in graphs. The first one is to find $k$ edge-disjoint forests in a directed graph $G$ of maximal size such that the indegree of each vertex in these forests is at most $k$. We describe a min-max characterization for this problem and show that it can be solved in almost linear time for fixed $k$, extending the algorithm of [Gabow, 1995]. Specifically, the complexity is $O(k δm \log n)$, where $n, m$ are the number of vertices and edges in $G$ respectively, and $δ= \max\{1, k - k_G\}$, where $k_G$ is the edge connectivity of the graph. Using our solution to this problem, we improve complexities for two existing applications: (1) $k$-forest problem: find $k$ forests in an undirected graph $G$ maximizing the number of edges in their union. We show how to solve this problem in $O(k^3 \min\{kn, m\} \log^2 n + k \cdot{\rm MAXFLOW}(m, m) \log n)$ time, breaking the $O_k(n^{3/2})$ complexity barrier of previously known approaches. (2) Directed edge-connectivity augmentation problem: find a smallest set of directed edges whose addition to the given directed graph makes it strongly $k$-connected. We improve the deterministic complexity for this problem from $O(k δ(m+δn)\log n)$ [Gabow, STOC 1994] to $O(k δm \log n)$. A similar approach with the same complexity also works for the undirected version of the problem.

Faster algorithms for packing forests in graphs and related problems

TL;DR

This work advances the theory and practice of packing forests in graphs by developing a min–max framework for the bounded-indegree k-forest problem and an almost linear-time algorithm for τ = 0, enabling efficient solutions for related problems. It then leverages this foundation to achieve faster algorithms for the undirected k-forest problem and for directed and undirected edge-connectivity augmentation, using auxiliary graphs, pseudoforests, and top-clump contractions. The central innovations include a precise min–max characterization, a robust augmenting-path scheme, and a structured reduction to extensions and edge-splitting that collectively break prior complexity barriers. The results have practical implications for routing, rigidity analysis, and network design, offering scalable and deterministic methods for constructing large collections of edge-disjoint forests and for augmenting connectivity.

Abstract

We consider several problems related to packing forests in graphs. The first one is to find edge-disjoint forests in a directed graph of maximal size such that the indegree of each vertex in these forests is at most . We describe a min-max characterization for this problem and show that it can be solved in almost linear time for fixed , extending the algorithm of [Gabow, 1995]. Specifically, the complexity is , where are the number of vertices and edges in respectively, and , where is the edge connectivity of the graph. Using our solution to this problem, we improve complexities for two existing applications: (1) -forest problem: find forests in an undirected graph maximizing the number of edges in their union. We show how to solve this problem in time, breaking the complexity barrier of previously known approaches. (2) Directed edge-connectivity augmentation problem: find a smallest set of directed edges whose addition to the given directed graph makes it strongly -connected. We improve the deterministic complexity for this problem from [Gabow, STOC 1994] to . A similar approach with the same complexity also works for the undirected version of the problem.
Paper Structure (29 sections, 30 theorems, 27 equations, 1 table, 5 algorithms)

This paper contains 29 sections, 30 theorems, 27 equations, 1 table, 5 algorithms.

Key Result

Theorem 1.1

There exists a deterministic algorithm for Problem the_one_problem with $\tau={\bf 0}$ that runs in $O(k \delta m \log n)$ time. Consequently, the problem can be solved in the same time for $\tau=\tau^{a:k}$ by applying the algorithm for $\tau={\bf 0}$ to the graph obtained from $G$ by removing all

Theorems & Definitions (48)

  • Theorem 1.1
  • Theorem 1.2
  • Theorem 1.3
  • Theorem 1.4
  • Theorem 2.1: frank
  • Definition 3.1: auxiliary graph
  • Theorem 3.2
  • Definition 3.3
  • Lemma 3.4
  • Corollary 3.5: Min-max characterization
  • ...and 38 more