English

Linear-Time MaxCut in Multigraphs Parameterized Above the Poljak-Turz\'ik Bound

Data Structures and Algorithms 2024-07-02 v1 Computational Complexity Discrete Mathematics

Abstract

MaxCut is a classical NP-complete problem and a crucial building block in many combinatorial algorithms. The famous Edwards-Erd\H{o}s bound states that any connected graph on n vertices with m edges contains a cut of size at least m/2+(n1)/4m/2 + (n-1)/4. Crowston, Jones and Mnich [Algorithmica, 2015] showed that the MaxCut problem on simple connected graphs admits an FPT algorithm, where the parameter k is the difference between the desired cut size c and the lower bound given by the Edwards-Erd\H{o}s bound. This was later improved by Etscheid and Mnich [Algorithmica, 2017] to run in parameterized linear time, i.e., f(k)O(m)f(k)\cdot O(m). We improve upon this result in two ways: Firstly, we extend the algorithm to work also for multigraphs (alternatively, graphs with positive integer weights). Secondly, we change the parameter; instead of the difference to the Edwards-Erd\H{o}s bound, we use the difference to the Poljak-Turz\'ik bound. The Poljak-Turz\'ik bound states that any weighted graph G has a cut of size at least w(G)/2+wMSF(G)/4w(G)/2 + w_{MSF}(G)/4, where w(G) denotes the total weight of G, and wMSF(G)w_{MSF}(G) denotes the weight of its minimum spanning forest. In connected simple graphs the two bounds are equivalent, but for multigraphs the Poljak-Turz\'ik bound can be larger and thus yield a smaller parameter k. Our algorithm also runs in parameterized linear time, i.e., f(k)O(m+n)f(k)\cdot O(m+n).

Keywords

Cite

@article{arxiv.2407.01071,
  title  = {Linear-Time MaxCut in Multigraphs Parameterized Above the Poljak-Turz\'ik Bound},
  author = {Jonas Lill and Kalina Petrova and Simon Weber},
  journal= {arXiv preprint arXiv:2407.01071},
  year   = {2024}
}

Comments

20 pages

R2 v1 2026-06-28T17:24:37.372Z